40 jobs found

Machine Learning Platform Engineering Manager We're Kingfisher, a team made up of over 74,000 passionate people bringing Kingfisher and our other brands - B&Q, Screwfix, Brico Dépôt, Castorama and Koctasto life - guided by our purpose: Better Homes. Better Lives. For Everyone. We believe a better world starts with better homes, and we work every day to make that a reality. Join us and help shape the future of home improvement. London, Southampton & Yeovil - Talk to us about how we can best support you! This is an opportunity to make a significant impact across one of the largest retail groups in Europe. We are looking for a Machine Learning Engineering Manager who can lead the productionisation of advanced AI solutions created by our Group AI team. Your work will help shape how millions of customers and colleagues experience our products, services and decision making. You will guide the delivery of real world Machine Learning systems across the business and help establish a strong engineering culture across our AI organisation. This role is suited to someone who is confident in both leadership and technical depth, with enthusiasm to champion the adoption of AI across the group. Key Accountabilities / Responsibilities Lead the delivery of major Artificial Intelligence projects and help drive the next stage of Machine Learning development within Kingfisher. Oversee multiple teams working across a wide range of business domains and ensure they deliver complete end to end Machine Learning solutions. Develop and support Machine Learning team leads who each manage domain based project teams. Build and guide diverse teams that can translate business needs into Machine Learning solutions and communicate recommendations clearly to non technical stakeholders. Create an environment of cross team collaboration and knowledge sharing in order to improve effectiveness across Group AI. Work closely with Technology, Product and Data colleagues to help shape the data platforms that enable us to embed Machine Learning into our products and operational processes. Act as a visible advocate for the use of Machine Learning within Kingfisher and help promote its value across the group. Support the wider data leadership team in developing a strong data culture and in demonstrating the importance of data informed decisions. Contribute to the development and recognition of the Group AI brand both inside and outside the organisation. Qualifications Strong leadership experience with the ability to build, mentor and organise high performing Machine Learning teams. Excellent stakeholder management skills with the ability to understand real business needs and influence senior decision makers. Solid grounding in computer science including algorithms, data structures, modelling and software architecture. Strong understanding of classical Machine Learning and modern Deep Learning methods. Good proficiency in SQL and Python and familiarity with the Python data ecosystem. Experience working with Generative AI and agent based frameworks such as LangChain or LangGraph. Clear understanding of the Machine Learning development lifecycle and MLOps principles. Proven experience delivering AI solutions into production environments including cloud based services. Confidence working with CI/CD, data pipelines and containerised deployments such as Kubernetes and Kubeflow. Strong communication skills and the ability to manage several technical projects simultaneously. Benefits We offer a competitive benefits package and ample opportunities to stretch and grow your career. Private Health Care - Opportunity to receive up to family level cover with AXA. Kingfisher Pension Scheme - Immediate eligibility through auto enrolment. Contribute 8% to receive a max 14% from the Company. 25 Days' Holiday - 25 days per annum plus bank holidays. Staff Discount - 20% discount at B&Q and Screwfix. Eligible after 3 months service. Kingfisher Share Incentive Plan (SIP) - Share ownership in a tax efficient way. Life Assurance - x4 Salary plus benefit equal to value of your Retirement Account. Bonus - Competitive bonus scheme that aligns to work level of role. Kingfisher Share Save - Option to buy Kingfisher plc shares at the end of a 3 or 5 year period. Diversity & Inclusion Our customers come from all walks of life - and so do we. We're committed to ensuring all colleagues, future colleagues, and applicants are treated equally, regardless of age, gender, marital or civil partnership status, ethnicity, culture, religion, belief, political opinion, disability, gender identity, gender expression, or sexual orientation. Company Kingfisher plc

Glasgow, GBR, G511DA London, GBR, W1A 1AA Newcastle-upon-Tyne, GBR, NE991RN Salford, GBR, M50 2QH JOB DETAILS Principal Data Scientist - Discoverability, Recommendations Job Reference: 43528 Band: D Salary: £73,000 - £83,000 depending on relevant skills, knowledge and experience. The expected salary range for this role reflects internal benchmarking and external market insights. Contract type: Permanent - Full Time Location: Salford, Glasgow, Newcastle, London. This is a hybrid role, and the successful candidate will balance office working with home working. We're happy to discuss flexible working. Please indicate your choice under the flexible working question in the application. There is no obligation to raise this at the application stage but if you wish to do so, you are welcome to. Flexible working will be part of the discussion at offer stage. PURPOSE OF THE ROLE The BBC has been serving audiences online for decades. Across our flagship products - BBC iPlayer, Sounds, News, Sport, and more - we educate, inform, and entertain millions of people every single day. We are now accelerating our shift towards experiences that are shaped around our audiences: more personal, more relevant, and more responsive to their needs. At the heart of this transformation is the Recommendations team. We design and build large scale ML/AI systems that help audiences discover the right content at the right moment. Our work already powers experiences across the BBC, including personalised recommendations on iPlayer and BBC Sounds. We're now looking for a Principal Data Scientist to help us in this next stage of our journey. WHY JOIN THE TEAM As a Principal Data Scientist, you'll play a key role in shaping the technical direction of recommender systems used by millions of people each day. You'll be a hands on contributor - prototyping, experimenting, and guiding the technical approach for complex ML solutions at true BBC scale. Working in a cross-functional team, you'll partner closely with engineers, product managers, and data scientists to deliver high impact systems that help audiences connect with the BBC's breadth and depth of content. Beyond your immediate team, you'll be an active member of the wider BBC Data Science community. You'll have opportunities to share your work, influence the development of data science and AI practices across the organisation, and engage with external communities to continue your own learning and development. YOUR KEY RESPONSIBILITIES AND IMPACT You'll use your technical skills to deliver value to BBC audiences, blending a breadth and depth of data science expertise. You'll have impact within your immediate team and beyond, across the wider BBC, instrumental in developing scalable ML products. You'll work effectively within a cross-functional environment, collaborating to overcome the real-world challenges of deploying and maintaining ML in production. You'll apply your knowledge of machine learning algorithms to solve complex user and business problems in a robust and scalable way. You'll join the wider BBC Data Science community, with internal and external opportunities to get involved, share your knowledge, and mentoring colleagues. YOUR SKILLS AND EXPERIENCE Extensive hands on experience in data science and machine learning, with a proven track record of contributing to technical machine learning projects. Experience developing and deploying recommender systems. Strong coding skills in Python. Ability to clearly communicate to both technical and non technical audiences. Ability to work effectively in a cross functional team. Experience with model lifecycle management and MLOps, including model deployment, versioning and monitoring. Good knowledge of cloud services, ideally AWS. Knowledge and understanding of best practices such as testing, code management and deployment. Mentorship and/or supervision of other team members. You are encouraged to apply even if you don't meet every one of the criteria above! We'll find above some of the skills and experience we expect from a Principal Data Scientist. Please do not think you have to tick all boxes: you will be working in a supportive and collaborative team, where we aim to put everyone in the condition to contribute at their best and feel that their work is useful and valued. Besides, you will find great development and learning opportunities to support your professional growth. We value diversity and are committed to be truly inclusive and a place where everyone belongs. APPLICATION PROCESS There is a 2-stage process: Hiring manager introductory call covering role background and candidate motivations for applying (external applicants only). 1.5 hour panel interview including a technical presentation from the candidate and role relevant competency-based questions. DISCLAIMER This job description is a written statement of the essential characteristics of the job, with its principal accountabilities, incorporating a note of the skills, knowledge and experience required for a satisfactory level of performance. This is not intended to be a complete, detailed account of all aspects of the duties involved. Please note: If you were to be offered this role, the BBC will conduct Employment screening checks which include Reference checks; Eligibility to work checks; and if applicable to the role, Safeguarding and Adverse media/Social media checks. Any offer made is conditional on these checks being satisfactory. Before your start date, you may need to disclose any unspent convictions or police charges, in line with our Recruitment policy. This allows us to discuss any support you may need and assess any risks. Failure to disclose may result in the withdrawal of your offer. The BBC is committed to redeploying employees seeking suitable alternative employment within the BBC and they will be given priority consideration ahead of other applicants. Priority consideration means for those employees seeking redeployment their application will be considered alongside anyone else at risk of redundancy, prior to any individuals being considered who are not at risk. DIVERSITY, INCLUSION & BELONGING We welcome applications from individuals, regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio economic background, religion and/or belief. DISABILITY CONFIDENT We are a disability confident employer. If you need to discuss adjustments or access requirements for the interview process, or to carry out this role, please contact us via email and we'd be happy to discuss: BENEFITS Fair pay and flexible benefits including a competitive salary package, a flexible 35-hour working week, 25 days annual leave with the option to buy an extra 5 days, a defined pensions scheme and discounted dental, health care and gym. Excellent career and professional development. Support in your working life, including flexible working which you can discuss with us at any point during the application, selection or offer. A values based organisation where the way we do things is important as what we do. Benefits may vary if you are joining on an FTC basis or on an orchestra conditions contract. BBC Group and Public Services, Broadcasting House, Portland Place, London, United Kingdom, W1A 1AA. BBC Studios Distribution Limited, company no: , registered address: 1 Television Centre, 101 Wood Lane, London, United Kingdom W12 7FA.

Make a real difference with your engineering and analytical skills. At SheerID, we're building the future of secure, data-driven marketing with our innovative Audience Data Platform. Our mission is to deliver a seamless verification experience for millions of users monthly, ensuring that exclusive offers reach the right people while proactively identifying and neutralizing sophisticated fraud. As a Principal Data Scientist, you'll play a critical role in architecting, developing, and deploying cutting edge fraud detection and prevention systems within our SaaS solutions. You will have a direct impact on SheerID's growth by safeguarding the integrity of our platform. You'll collaborate with a high performing team to build scalable, real time models that distinguish between genuine users and bad actors. You'll not only build sophisticated defense systems but also mentor colleagues, conduct technical reviews, and lead the charge in staying ahead of evolving fraud tactics. We're seeking a passionate and experienced data science leader with a deep foundation in anomaly detection, pattern recognition, and machine learning. You thrive in collaborative environments, possess strong leadership qualities, and are committed to crafting high quality, secure software that protects our clients and their customers from digital deception. Role Specific Job Duties Architect Fraud Solutions: Partner with product & engineering to design and implement high performance, scalable AI/ML models to detect and prevent fraud in data intensive applications. Drive Innovation: Champion best practices and explore emerging technologies to enhance the fraud detection platform. Mentor and Lead: Provide technical leadership through architectural reviews and mentorship, fostering a culture of automation and continuous learning. Influence Strategy: Partner with product and engineering leadership to define the roadmap, balancing model scaling with reliability trade offs. Solve Complex Challenges: Act as the technical escalation point for the "hairiest" problems, from data quality issues to model performance bottlenecks. Own the Lifecycle: Manage projects from design and development to deployment, monitoring, and post mortem analysis. Collaborate Cross Functionally: Translate complex business requirements and research into robust, production ready AI solutions alongside engineers and product managers. Required Skills / Experience Bachelor's degree in Computer Science, Software Engineering, Statistics, Mathematics, or a related quantitative field (equivalent experience considered). 20+ years of relevant experience in data science, with a strong focus on predictive fraud analytics and large scale data applications. Proven ability to design, develop, and deploy scalable and maintainable machine learning models in a production environment. Deep understanding of statistical methods, machine learning algorithms, and advanced data mining techniques. Proficiency in a statistical/general programming language (e.g., Python, R, Scala), with extensive experience with relevant libraries and frameworks. Expertise in debugging complex data issues and model performance problems. Exceptional communication, interpersonal, and problem solving skills, with a demonstrated ability to influence and lead across teams. Strong foundational knowledge of data architecture/data warehousing and a track record of execution. Preferred Experience Expertise with Big Data, Data Science, or Stream Processing techniques. Experience applying advanced AI models, including computer vision and deep learning, to solve real world problems. Experience with AWS, Kubernetes, VertexAI, Labelbox, and MLOps practices. Experience with SQL and NoSQL databases (MongoDB, Elasticsearch, etc.). Experience with graph analysis and network science for fraud detection. Experience with automated data processing pipelines and feature engineering at scale. SheerID is an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We celebrate diversity and are committed to creating an inclusive environment for all candidates and employees. SheerID believes that diversity and inclusion is critical to our success as a company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool.

Key Responsibilities Define and lead a comprehensive AI strategy for Janus Henderson, continuously refining it based on emerging technologies and business needs. Lead a team of data scientists and AI engineers to develop predictive models and AI solutions, guiding the model development life cycle from proof of concept to deployment. Establish and enforce an AI governance framework, including model validation, transparency, fairness, and compliance with emerging AI regulations. Encourage collaboration across business units, embedding AI solutions into processes and supporting integration with technology teams. Monitor industry trends, evaluate new AI techniques and fintech innovations, and lead pilot programs to assess ROI and advocate for strategic investments in data science capabilities. Required Qualifications Master's or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or related quantitative field. 10+ years of experience in data science or analytics, with at least 5 years in a leadership or managerial capacity, preferably in financial services or asset management. Deep expertise in machine learning and statistical modeling, hands on experience developing and deploying models (e.g., predictive models, NLP, time series forecasting) and managing model risk in a regulated environment. Solid understanding of asset management business, including investment products, portfolio management, performance analytics and regulatory compliance reporting. Demonstrated leadership and communication skills, with the ability to articulate complex analytical findings to senior executives and to influence decision making. Preferred Experience Direct experience within an asset management analytics or quantitative research team. Hands on experience establishing governance processes for AI/ML and familiarity with EU AI Act, SEC guidance on model risk and ethical AI frameworks. Proficiency with advanced analytics libraries and tools used in finance, including quantitative finance libraries, time series databases and visualization platforms such as Tableau or Power BI. Published work, patents or conference presentations related to AI or data science in finance. Technical Skills Programming: Python (pandas, scikit learn, TensorFlow/PyTorch), R, SQL, Jupyter notebooks and version control (Git). Machine Learning: regression, classification, clustering, tree based models, neural networks, MLOps practices and model deployment. Data Platforms: relational and NoSQL databases, time series stores, cloud data services (AWS Redshift, Azure Synapse, Google BigQuery) and distributed computing frameworks. Analytics & BI: Tableau, Power BI, matplotlib/Plotly, Excel or similar tools for data storytelling. AI Ethics & Security: bias detection, explainability (LIME, SHAP), data anonymization, encryption and secure data enclaves. Soft Skills & Leadership Competencies Strategic vision for AI and analytics, communicating the vision to senior leaders. High ethical standards, advocating responsible AI and refusing use cases that pose undue risk. Exceptional storytelling ability, translating complex insights into plain language for non technical audiences. Collaborative influence across IT, investment, compliance and client teams. Mentorship, fostering continuous learning and recruiting top talent. Problem solving resilience, systematically addressing data quality, model performance and resource constraints. What to Expect When You Join Hybrid working with reasonable accommodations. Generous holiday policies and paid volunteer time. Professional development support, tuition reimbursement and continuing education. All inclusive diversity, equity and inclusion culture. Maternal/paternal leave benefits and family services. Access to Headspace, ClassPass and other well being benefits. Unique employee events, including health challenges and evening socials. Supervisory Responsibilities Yes Potential for Growth Mentoring programs Leadership development Regular training sessions Career development services Continuing education courses Regulatory & Ethical Expectations You will be expected to understand the regulatory obligations of the firm and abide by JHI policies applicable to your role, including adherence to the Investment Advisory Code of Ethics. Annual Bonus Opportunity Position may be eligible for an annual discretionary bonus award from the profit pool, with individual awards based on company, department, team and personal performance. Benefits Summary Comprehensive total rewards package including competitive compensation, pension/retirement plans, health and well being benefits, and flexible work arrangements. Equal Opportunity Statement Janus Henderson Investors is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. All applications are subject to background checks.

Overview The Head of Data Science & AI spearheads Janus Henderson's data driven initiatives, leading the development and execution of a strategy that harnesses data and artificial intelligence across the organization. The role oversees advanced analytics, AI model development, and AI/ML governance, ensuring that AI is applied ethically and effectively to enhance investment research, client experience, and operations while maintaining the firm's standards of accuracy, transparency, and trust. Key Responsibilities AI Strategy: Define and lead a comprehensive AI strategy aligned with business objectives, continuously refining it based on emerging technologies and evolving needs. Model Development & AI Innovation: Lead a team of data scientists and AI engineers to develop predictive models and AI solutions, guiding the model lifecycle from proof of concept to production and ensuring ongoing value and maintenance. AI Governance & Ethics: Establish and enforce an AI governance framework, including model validation, transparency, fairness, and compliance with emerging AI regulations. Enablement & Collaboration: Act as a bridge between the Data Science team and other business units, fostering integration of AI solutions into processes and working closely with technology leaders. Emerging Technology & Thought Leadership: Monitor industry trends, evaluate new AI techniques, pilot innovations, and advocate for investments that deliver competitive advantage and risk reduction. Required Qualifications Education: Master's or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field. Experience: 10+ years in data science, analytics, or related technology roles, with a minimum of 5 years in leadership or managerial capacity. Experience in financial services, asset management, or capital markets is highly desirable. Technical Proficiency: Deep expertise in machine learning techniques, statistical modeling, and large dataset analytics; proven track record of model development and deployment. Industry Knowledge: Solid understanding of asset management products, portfolio management, performance analytics, and client servicing; awareness of how AI is applied in investment management. Leadership & Communication: Demonstrated ability to lead multidisciplinary teams, manage complex projects, and convey analytical insights to senior executives. Preferred Experience Direct experience in an asset management analytics or quantitative research team. Established AI/ML governance processes, including model review committees and monitoring frameworks. Familiarity with advanced analytics ecosystems in finance (e.g., quantitative libraries, time series databases, visualization tools). Published research, patents, or conference presentations in AI or data science related to finance. Technical Skills Programming: Python (pandas, scikit learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree based models, neural networks; MLOps, model deployment, automated testing. Data Platforms: relational databases, NoSQL, time series, big data frameworks, cloud data services (AWS, Azure, GCP). Analytics & BI: Tableau, Power BI, Python/R visualization, statistical analysis tools. AI Ethics & Security: bias detection, explainability (LIME, SHAP), data anonymization, encryption. Soft Skills & Leadership Competencies Strategic Vision & Innovation Ethical Leadership & Responsible AI advocacy Storytelling & Communication for non technical audiences Collaboration & Influence across organizational boundaries Mentorship & Talent Development Problem Solving & Resilience Benefits and Working Conditions Hybrid working environment with reasonable accommodations Generous holiday policy Paid volunteer time Professional development support (courses, tuition reimbursement) Inclusive diversity, equity, and inclusion initiatives Family leave benefits Well being initiatives (Headspace, ClassPass) Employee events and wellness perks (complimentary beverages, happy hours) Janus Henderson is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. All applications are subject to background checks. Applicants must comply with the firm's Investment Advisory Code of Ethics and any relevant regulatory obligations.

About Us At Plentific, we're redefining property management in real time. Our mission is to lead real estate through the transformative journey into "The World of Now," enabling us to empower property professionals through our innovative, cloud-based platform. We harness cutting-edge technology and data-driven insights to streamline operations for landlords, letting agents, and property managers-enabling them to optimize maintenance, manage repairs, and make informed decisions instantly. Our platform is designed to create seamless, real-time workflows that transform traditional property management into a dynamic, digital experience. Backed by a world-class group of investors-including Noa, Highland Europe, Brookfields, Mubadala, RXR Digital Ventures, and Target Global-Plentific is at the forefront of the proptech revolution. Headquartered in London with a global outlook, we're continually expanding our reach and impact. We're looking for forward-thinking, passionate professionals who are ready to contribute to our mission and drive industry innovation. If you're excited about making an immediate impact and shaping the future of property management, explore career opportunities with us at Plentific. The Role As an AI Applied Engineer, you will design, build, and deploy AI-powered features and automation tools that transform how our users interact with our platform and improve internal operational efficiency. You'll work across the stack to integrate AI capabilities-such as intelligent assistants, AI agents, and predictive systems-directly into our Python-based applications, experimenting with new frameworks and deployment solutions along the way. Your day-to-day will focus on building real, production-grade AI systems that deliver measurable value-whether that's automating property management workflows, creating decision-support tools for our teams, or embedding natural language and vision capabilities into our products. You'll collaborate closely with product managers, data scientists, and other engineers, taking AI solutions from concept to scalable production deployment. You'll have the freedom to explore cutting-edge tools like FastAPI, PydanticAI, LLM orchestration frameworks, while ensuring solutions are robust, maintainable, and secure. Responsibilities Develop and deploy AI-powered features and services in our Python-based stack (FastAPI and Django, DRF) and explore new frameworks (e.g. BentoML) for performance and scalability. Build and integrate intelligent automation systems, AI agents, and decision-support tools into core product workflows. Implement and optimise LLM-based systems, RAG pipelines, and AI agent architectures for complex property management workflows. Work with cross-functional teams to gather requirements, define AI use cases, and iterate quickly on prototypes. Integrate complementary AI capabilities-such as voice processing, computer vision, and NLP-into customer-facing and internal tools. Ensure all AI applications and models adhere to security best practices, including input validation, secure handling of sensitive data (PII/confidential property information), and protection against prompt injection and other AI-specific vulnerabilities. Collaborate with MLOps and platform engineers to ensure models are deployed, monitored, and iterated in production environments. Maintain clear documentation for AI systems, APIs, and workflows. Stay on top of emerging AI frameworks and deployment tools, bringing forward innovative ideas for application. Experience & Qualifications Strong Python development background (5+ years preferred), with solid experience in FastAPI or Django and Django REST Framework. Proven track record of building and deploying AI/ML-powered applications in production environments. Proficiency with async and streaming APIs, enabling efficient real-time data processing and low-latency AI service delivery in microservices (FastAPI, Django, Flask, or similar). Strong understanding of context engineering practices, optimising prompts, memory, and retrieval strategies for LLM-based systems. Hands-on experience with AI-assisted development tools such as Cursor, Claude Code, Codex, and GitHub Copilot, focusing on AI specification-driven approaches for technical analysis, code generation, and code review. Hands-on experience with AI/ML frameworks (PyTorch, TensorFlow, HuggingFace) and LLM orchestration tools (PydanticAI, LangChain, LangGraph, or similar) Experience deploying ML models using containerised solutions (Docker, Kubernetes) and frameworks like BentoML or equivalent. Familiarity with vector databases and retrieval pipelines for RAG architectures. Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps tooling (MLflow, Kubeflow, or similar). Familiarity with voice-to-text, IVR, and/or computer vision systems is a plus. Strong understanding of software engineering best practices-testing, CI/CD, version control, code reviews. Excellent problem-solving skills and ability to collaborate in cross-functional teams. Benefits As you can see, we are quickly progressing with our ambitious plans and are eager to grow our team of doers to achieve our vision of managing over 2 million properties through our platform across various countries. You can help us shape the future of property management across the globe. Here's what we offer: A competitive compensation package 25 days annual holiday + 1 additional day for every year served up to 3 years. Flexible working environment including the option to work abroad Private health care for you and immediate family members with discounted gym membership, optical, dental and private GP Enhanced parental leave Life insurance (4x salary) Employee assistance program Company volunteering day and charity salary sacrifice scheme Learning management system powered by Udemy Referral bonus and charity donation if someone you introduce joins the company Season ticket loan, Cycle to work, Electric vehicle and Techscheme programs Pension scheme Work abroad scheme Company-sponsored lunches, dinners and social gatherings Fully stocked kitchen with drinks, snacks, fruit, breakfast cereal etc.

Head of Engineering About H: H exists to push the boundaries of superintelligence with agentic AI. By automating complex, multi-step tasks typically performed by humans, AI agents will help unlock full human potential. H is hiring the world's best AI talent, seeking those who are dedicated as much to building safely and responsibly as to advancing disruptive agentic capabilities. We promote a mindset of openness, learning, and collaboration, where everyone has something to contribute. Responsibilities Own, review, and challenge the end-to-end architecture of our product and research stack, including inference systems and the agent platform. Scale and lead the Product Engineering, Infrastructure, and Inference teams, with clear ownership, execution rigor, and strong technical standards. Partner closely with Product, Research, and Leadership to translate strategy into reliable, scalable systems. Must-have experience Proven track record building and scaling a production SaaS platform. Strong hands-on experience with AWS, Docker, Kubernetes, Redis, and modern observability tooling (e.g. Datadog). Exposure to MLOps, large-scale model training, inference systems, or LLM-based reinforcement learning. Experience operating multi-tenant systems with high reliability, security, and performance. Experience building and deploying enterprise platforms self-hosted or on-premise. Familiarity with SOC 2 or similar compliance frameworks in a production environment. Nice-to-have experience Experience orchestrating compute-intensive workloads (training and/or large-scale inference). Familiarity with workflow orchestration platforms. Location Paris or London. This role is hybrid, and you are expected to be in the office 3 days a week on average. Please expect some travel between offices on a reasonable cadence (e.g., every 4-6 weeks). What We Offer Join the exciting journey of shaping the future of AI, and be part of the early days of one of the hottest AI startups. Collaborate with a fun, dynamic, and multicultural team, working alongside world-class AI talent in a highly collaborative environment. Enjoy a competitive salary. Unlock opportunities for professional growth, continuous learning, and career development.

Please note this role is offered as an initial 6 month fixed term contract on a PAYE basis Lyst is a global fashion shopping platform founded in London in 2010 and catering to over 160M shoppers per year. We offer our customers the largest assortment of premium & luxury fashion products in one place, curating pieces from 27,000 of the world's leading brands and stores. In 2025, Lyst joined Zozo, operators of Zozotown, the leading fashion e commerce platform in Japan. This partnership marks a bold new era for Lyst, as we accelerate our vision and work together to transform the future of fashion shopping through AI and technology. At Lyst, we obsess over the customer, providing a search & discovery experience which offers inspiration, fulfilment, and personalisation. We believe that fashion is amazing but shopping for fashion often isn't, and use our technology, data and creativity to bring more joy, greater choice and fewer fails. Our mission is to help fashion shoppers make better choices and help fashion partners find better audiences as the category leading destination for every fashion shopper. The Role We're looking for a technically strong Product Manager to lead our Affiliate Operations product team, and be the primary Lyst owner for our partnership with ZOZO's Data Science team in New Zealand. Lyst became part of the ZOZO group last year, and this role will work closely with ZOZO's R&D teams to turn research into productionised product data improvements. You will be accountable for the quality, reliability and discoverability of the world's largest product catalogue, powering discovery and commerce across Lyst. Crucially, you will also support Lyst's commercial initiatives from a TPM perspective - shaping the product and data work to accelerate product merging and enrichment. You'll be the lead Lyst contact for ZOZO's Data Science department and will run regular meetings, define joint milestones and translate data science research into Lyst production work. Together you'll accelerate product merging and enrichment while ensuring tooling is production ready. This role is highly cross functional and strategic. If you enjoy being technical, shipping data products, and managing a data science partnership to deliver measurable business outcomes, this is for you. What you'll own Affiliate Operations strategy & roadmap - Prioritise initiatives that raise data quality, completeness and coherence, and ensure delivery of outcomes that improve discovery and checkout metrics. Data foundations & pipelines - Working with engineering, to define product data models and taxonomies and own product data quality KPIs and remediation workflows. Ensure enrichment and merging flows are implemented and monitored. Partnership with ZOZO Data Science (NZ) - Be the primary Lyst lead managing the relationship with ZOZO's data science team: align roadmaps, define experiments, translate research into production requirements, agree on data contracts/security/IP terms, and run regular syncs and reviews. ZOZO collaboration is a core part of our product enrichment work. Operational ownership - Set and measure SLAs for data freshness, accuracy and output quality. Ensure handoffs and runbooks for the Affiliate Operations team are clear. Commercial & stakeholder management - Liaise with Partnerships and Commercial teams to align product data priorities to business objectives (e.g. ROAS bidding algorithms). People & process - Lead the Affiliate Operations product practice: improve team rituals, prioritisation and delivery cadence. Day to day responsibilities Create and maintain an outcome driven roadmap for Affiliate Operations and our commercial roadmap. Translate ZOZO data science outputs (enrichments/merges/flags) into production requirements, APIs and acceptance criteria. Run regular cross organisation planning with ZOZO and Affiliate Operations, including quarterly planning and technical workshops; manage time zone differences and ensure clear asynchronous handovers. Define and track OKRs tied to listings quality and commercial outcomes. Build the backlog and intake process for operational work, tooling requests and BAU. Communicate progress and trade offs clearly to senior stakeholders. Qualifications 3-6+ years product management experience, with a technical/data focus (hands on TPM or Senior TPM). Strong technical literacy: comfortable with APIs, data schemas, ETL/ingestion pipelines and product data modelling. Experience working with data scientists and engineering teams to productise models and features for production. Proven stakeholder management and delivery track record - you can run complex cross functional projects and manage external technical partners. Excellent written and verbal communication; experience coordinating across time zones and cultures. Agile delivery experience and a bias toward measurable outcomes. Nice to have Experience in ecommerce marketplaces or affiliate commerce. Exposure to machine learning/MLops or productionising ML models. Prior experience working with an external data science partner or international R&D partner. Familiarity with taxonomy design, entity resolution and image/data enrichment workstreams. Experience working with affiliate operations or merchant operations teams. Our Ways of Working Office Days: We all come into the office on Tuesdays and Thursdays, with the option to work remotely or come into the office on the other days. Time Off: In addition to the 8 statutory bank holidays, you will receive 29 holidays per year. Lyst's holiday year runs from 1 April to 31 March. Remote Working: Work from anywhere for up to 4 weeks per year. Competitive Family Leave Package: This includes Enhanced Family Leave for those eligible, paid Time off for Dependents and Support for Fertility Treatment & Loss. Clothing Benefit: We provide you with a clothing allowance to use on Lyst every year. This starts at £250 when you join and increases up to £1,000 with your length of service. Private Healthcare: Our healthcare provider is Vitality. Your health is important to us which is why we offer all employees a comprehensive healthcare scheme from the day you start. Training Allowance: All employees are entitled to an annual training allowance of £1,000 for conferences, industry events, training courses and to purchase resources. Pension Scheme: Our pension provider is The People's Pension. We offer a minimum employee contribution of 5% and 3% employer contribution. Eye Tests and Vouchers: Employees can make a saving on their eye test and glasses through our chosen provider. You'll receive a free eye test every year and a discount towards glasses. Cycle-to-Work Scheme: Lyst will purchase a bicycle from your chosen retailer, and you will receive a voucher to pick up your bicycle from them. Transport Season Ticket Loan: Employees can apply for an interest free season ticket loan to support your travel to work. Social Events: Frequent company wide social events including Christmas & summer parties, sports days, themed drinks, quizzes, cook alongs, as well as smaller team socials. We also have plenty of interest based groups such as football, running club, book club, culinary and more.

Please note this role is offered as an initial 6 month fixed term contract on a PAYE basis Lyst is a global fashion shopping platform founded in London in 2010 and catering to over 160M shoppers per year. We offer our customers the largest assortment of premium & luxury fashion products in one place, curating pieces from 27,000 of the world's leading brands and stores. In 2025, Lyst joined Zozo, operators of Zozotown, the leading fashion e commerce platform in Japan. This partnership marks a bold new era for Lyst, as we accelerate our vision and work together to transform the future of fashion shopping through AI and technology. At Lyst, we obsess over the customer, providing a search & discovery experience which offers inspiration, fulfilment, and personalisation. We believe that fashion is amazing but shopping for fashion often isn't, and use our technology, data and creativity to bring more joy, greater choice and fewer fails. Our mission is to help fashion shoppers make better choices and help fashion partners find better audiences as the category leading destination for every fashion shopper. The Role We're looking for a technically strong Product Manager to lead our Affiliate Operations product team, and be the primary Lyst owner for our partnership with ZOZO's Data Science team in New Zealand. Lyst became part of the ZOZO group last year, and this role will work closely with ZOZO's R&D teams to turn research into productionised product data improvements. You will be accountable for the quality, reliability and discoverability of the world's largest product catalogue, powering discovery and commerce across Lyst. Crucially, you will also support Lyst's commercial initiatives from a TPM perspective - shaping the product and data work to accelerate product merging and enrichment. You'll be the lead Lyst contact for ZOZO's Data Science department and will run regular meetings, define joint milestones and translate data science research into Lyst production work. Together you'll accelerate product merging and enrichment while ensuring tooling is production ready. This role is highly cross functional and strategic. If you enjoy being technical, shipping data products, and managing a data science partnership to deliver measurable business outcomes, this is for you. What you'll own Affiliate Operations strategy & roadmap - Prioritise initiatives that raise data quality, completeness and coherence, and ensure delivery of outcomes that improve discovery and checkout metrics. Data foundations & pipelines - Working with engineering, to define product data models and taxonomies and own product data quality KPIs and remediation workflows. Ensure enrichment and merging flows are implemented and monitored. Partnership with ZOZO Data Science (NZ) - Be the primary Lyst lead managing the relationship with ZOZO's data science team: align roadmaps, define experiments, translate research into production requirements, agree on data contracts/security/IP terms, and run regular syncs and reviews. ZOZO collaboration is a core part of our product enrichment work. Operational ownership - Set and measure SLAs for data freshness, accuracy and output quality. Ensure handoffs and runbooks for the Affiliate Operations team are clear. Commercial & stakeholder management - Liaise with Partnerships and Commercial teams to align product data priorities to business objectives (e.g. ROAS bidding algorithms). People & process - Lead the Affiliate Operations product practice: improve team rituals, prioritisation and delivery cadence. Day to day responsibilities Create and maintain an outcome driven roadmap for Affiliate Operations and our commercial roadmap. Translate ZOZO data science outputs (enrichments/merges/flags) into production requirements, APIs and acceptance criteria. Run regular cross organisation planning with ZOZO and Affiliate Operations, including quarterly planning and technical workshops; manage time zone differences and ensure clear asynchronous handovers. Define and track OKRs tied to listings quality and commercial outcomes. Build the backlog and intake process for operational work, tooling requests and BAU. Communicate progress and trade offs clearly to senior stakeholders. Qualifications 3-6+ years product management experience, with a technical/data focus (hands on TPM or Senior TPM). Strong technical literacy: comfortable with APIs, data schemas, ETL/ingestion pipelines and product data modelling. Experience working with data scientists and engineering teams to productise models and features for production. Proven stakeholder management and delivery track record - you can run complex cross functional projects and manage external technical partners. Excellent written and verbal communication; experience coordinating across time zones and cultures. Agile delivery experience and a bias toward measurable outcomes. Nice to have Experience in ecommerce marketplaces or affiliate commerce. Exposure to machine learning/MLops or productionising ML models. Prior experience working with an external data science partner or international R&D partner. Familiarity with taxonomy design, entity resolution and image/data enrichment workstreams. Experience working with affiliate operations or merchant operations teams. Our Ways of Working Office Days: We all come into the office on Tuesdays and Thursdays, with the option to work remotely or come into the office on the other days. Time Off: In addition to the 8 statutory bank holidays, you will receive 29 holidays per year. Lyst's holiday year runs from 1 April to 31 March. Remote Working: Work from anywhere for up to 4 weeks per year. Competitive Family Leave Package: This includes Enhanced Family Leave for those eligible, paid Time off for Dependents and Support for Fertility Treatment & Loss. Clothing Benefit: We provide you with a clothing allowance to use on Lyst every year. This starts at £250 when you join and increases up to £1,000 with your length of service. Private Healthcare: Our healthcare provider is Vitality. Your health is important to us which is why we offer all employees a comprehensive healthcare scheme from the day you start. Training Allowance: All employees are entitled to an annual training allowance of £1,000 for conferences, industry events, training courses and to purchase resources. Pension Scheme: Our pension provider is The People's Pension. We offer a minimum employee contribution of 5% and 3% employer contribution. Eye Tests and Vouchers: Employees can make a saving on their eye test and glasses through our chosen provider. You'll receive a free eye test every year and a discount towards glasses. Cycle-to-Work Scheme: Lyst will purchase a bicycle from your chosen retailer, and you will receive a voucher to pick up your bicycle from them. Transport Season Ticket Loan: Employees can apply for an interest free season ticket loan to support your travel to work. Social Events: Frequent company wide social events including Christmas & summer parties, sports days, themed drinks, quizzes, cook alongs, as well as smaller team socials. We also have plenty of interest based groups such as football, running club, book club, culinary and more.