Expedia, Inc.
Director, Machine Learning Science - Content AI Our Technology Team partners with teams across Expedia Group to create innovative products, services, and tools that deliver high-quality experiences for travelers, partners, and our employees. A single technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction. Introduction to the Team We're seeking a Director of Machine Learning Science to lead our Content AI strategy and execution. In this pivotal role, you will move beyond traditional ML applications to architect the next generation of our Content Engine. You will leverage Large Language Models (LLMs), Multimodal Modality, Agentic Workflow to ensure that every image, review, property description, and video is not only relevant but inspiring, safe, and hyper-personalized. Responsibilities Define the Content AI Strategy: Establish the technical roadmap and OKRs for the Machine Learning systems that power Content Generation, Content Moderation, and Content Relevance across our global ecosystem. Lead AI Innovation: Spearhead the deployment of cutting edge AI solutions (LLMs, Diffusion Models) to automate content creation (text, image, video) and summarization, enhancing discovery on both app and web platforms. Pioneer Agentic Workflows: Drive the research and development of autonomous AI Agents capable of reasoning over vast content repositories to answer complex traveler queries and perform multi-step planning tasks. Master Content Relevance & Safety: Oversee the development of models that rank and personalize content to improve conversion and loyalty, while simultaneously building robust automated moderation pipelines to ensure brand safety, trust, and quality at scale. Bridge the Gap between Research & Product: Prioritize efforts between foundational platform migration/optimization and cutting edge experimentation with new GenAI features. Influence & Collaborate: Foster cross functional partnerships with Product, Engineering, Legal, and Supply teams to integrate AI generated content into the core user experience seamlessly. Build a World Class Team: Recruit, mentor, and manage a high performing team of Applied Scientists and AI Engineers, fostering a culture of technical excellence and rapid experimentation. Minimum Qualifications Graduate degree (PhD preferred) in Computer Science, Artificial Intelligence, Computational Linguistics, or equivalent experience. 12+ years of experience in Machine Learning Science with a specific focus on NLP, Computer Vision, or Recommender Systems. 5+ years of people management experience, with a track record of leading high performing science teams in a tech first environment. Hands on experience with Generative AI technologies (e.g., Transformer architectures, LLMs like LLaMA/GPT, RAG pipelines, PEFT/LoRA fine tuning). Understanding of hallucination, latency, and cost optimization. Proven experience in the Content ML/AI space, specifically regarding Content Understanding, Moderation, Generation, and Relevance, creating rich and immersive user experiences. A proven track record of taking high risk, high reward ML projects from proof of concept to large scale production serving millions of users. Preferred Qualifications Agentic AI Experience: Experience building and deploying Agentic workflows with tool use, planning, and reasoning capabilities. Ability to translate complex AI concepts into clear business value for executive stakeholders. Pay Range: Total cash base $242,000.00 to $338,500.00 in San Jose. Potential to increase salary up to $387,000.00 based on performance. Starting pay varies by location, budget, and experience. Benefits: medical/dental/vision, paid time off, Employee Assistance Program, wellness & travel reimbursement, travel discounts, International Airlines Travel Agent membership. View our full list of benefits. Accommodation Requests If you need assistance with any part of the application or recruiting process due to a disability or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request. Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.
Director, Machine Learning Science - Content AI Our Technology Team partners with teams across Expedia Group to create innovative products, services, and tools that deliver high-quality experiences for travelers, partners, and our employees. A single technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction. Introduction to the Team We're seeking a Director of Machine Learning Science to lead our Content AI strategy and execution. In this pivotal role, you will move beyond traditional ML applications to architect the next generation of our Content Engine. You will leverage Large Language Models (LLMs), Multimodal Modality, Agentic Workflow to ensure that every image, review, property description, and video is not only relevant but inspiring, safe, and hyper-personalized. Responsibilities Define the Content AI Strategy: Establish the technical roadmap and OKRs for the Machine Learning systems that power Content Generation, Content Moderation, and Content Relevance across our global ecosystem. Lead AI Innovation: Spearhead the deployment of cutting edge AI solutions (LLMs, Diffusion Models) to automate content creation (text, image, video) and summarization, enhancing discovery on both app and web platforms. Pioneer Agentic Workflows: Drive the research and development of autonomous AI Agents capable of reasoning over vast content repositories to answer complex traveler queries and perform multi-step planning tasks. Master Content Relevance & Safety: Oversee the development of models that rank and personalize content to improve conversion and loyalty, while simultaneously building robust automated moderation pipelines to ensure brand safety, trust, and quality at scale. Bridge the Gap between Research & Product: Prioritize efforts between foundational platform migration/optimization and cutting edge experimentation with new GenAI features. Influence & Collaborate: Foster cross functional partnerships with Product, Engineering, Legal, and Supply teams to integrate AI generated content into the core user experience seamlessly. Build a World Class Team: Recruit, mentor, and manage a high performing team of Applied Scientists and AI Engineers, fostering a culture of technical excellence and rapid experimentation. Minimum Qualifications Graduate degree (PhD preferred) in Computer Science, Artificial Intelligence, Computational Linguistics, or equivalent experience. 12+ years of experience in Machine Learning Science with a specific focus on NLP, Computer Vision, or Recommender Systems. 5+ years of people management experience, with a track record of leading high performing science teams in a tech first environment. Hands on experience with Generative AI technologies (e.g., Transformer architectures, LLMs like LLaMA/GPT, RAG pipelines, PEFT/LoRA fine tuning). Understanding of hallucination, latency, and cost optimization. Proven experience in the Content ML/AI space, specifically regarding Content Understanding, Moderation, Generation, and Relevance, creating rich and immersive user experiences. A proven track record of taking high risk, high reward ML projects from proof of concept to large scale production serving millions of users. Preferred Qualifications Agentic AI Experience: Experience building and deploying Agentic workflows with tool use, planning, and reasoning capabilities. Ability to translate complex AI concepts into clear business value for executive stakeholders. Pay Range: Total cash base $242,000.00 to $338,500.00 in San Jose. Potential to increase salary up to $387,000.00 based on performance. Starting pay varies by location, budget, and experience. Benefits: medical/dental/vision, paid time off, Employee Assistance Program, wellness & travel reimbursement, travel discounts, International Airlines Travel Agent membership. View our full list of benefits. Accommodation Requests If you need assistance with any part of the application or recruiting process due to a disability or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request. Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.
Huron Consulting Group Inc.
City, Belfast
Data Science Manager page is loaded Data Science Managerremote type: Hybridlocations: Belfast - 20 Adelaide Streetposted on: Posted Todayjob requisition id: JR-Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future. Join our team as the expert you are now and create your future. Data Science Manager We're seeking a Data Science Manager to join the Data Science & Machine Learning team in our Commercial Digital practice, where you'll lead advanced analytics initiatives that transform how Fortune 500 companies make decisions across Financial Services, Manufacturing, Energy & Utilities, and other commercial industries.Managers play a vibrant, integral role at Huron. Their invaluable knowledge reflects in the projects they manage and the teams they lead. Known for building long-standing partnerships with clients, they collaborate with colleagues to solve their most important challenges. Our Managers also spend significant time mentoring junior staff on the engagement team-sharing expertise, feedback, and encouragement. This promotes a culture of respect, unity, collaboration, and personal achievement.This isn't a reporting role or a dashboard factory-you'll own the full analytics lifecycle from hypothesis formulation through insight delivery, while leading and developing a team of data scientists and analysts. You'll work on problems that matter: experimental designs that validate multi-million-dollar strategies, predictive models that surface hidden patterns in complex data, and deep learning pipelines that extract signal from unstructured text, images, and time-series. Our clients are Fortune 500 companies looking for partners who can find the signal in the noise and tell the story that drives action.The variety is real. In your first year, you might lead a customer segmentation and lifetime value analysis for a financial services firm, design and analyze a pricing experiment for a global manufacturer, and build an agentic anomaly detection system for a utility company's operational data-all while developing the next generation of data science talent at Huron. If you thrive on rigorous analysis, clear communication of complex findings, and building high-performing teams, this role is for you.# What You'll Do Lead and mentor junior data scientists and analysts -provide technical guidance, review analytical approaches and code, and support professional development. Foster a culture of intellectual curiosity, rigorous methodology, and clear communication within the team. Manage complex multi-workstream analytics projects -oversee project planning, resource allocation, and delivery timelines. Ensure analyses meet quality standards and client expectations while maintaining methodological rigor. Design and execute end-to-end data science workflows -from problem framing and hypothesis development through exploratory analysis, modeling, validation, and insight delivery. Own the analytical approach and ensure conclusions are defensible. Lead development of both traditional statistical and modern AI-powered analyses -including regression, classification, clustering, causal inference, A/B testing, and modern deep learning approaches using embeddings, transformer architectures, and foundation models for text, time-series, and multimodal analysis. Build predictive and prescriptive models that drive business decisions-customer segmentation, churn prediction, demand forecasting, pricing optimization, risk scoring, and operational efficiency analysis for commercial enterprises. Translate complex analytical findings into actionable insights -create compelling data narratives, develop executive-ready presentations, and communicate technical results to non-technical stakeholders in ways that drive decisions. Serve as a trusted advisor to clients -build long-standing partnerships, deeply understand business problems, formulate the right analytical questions, and deliver insights that create measurable value. Contribute to practice development -participate in business development activities, develop reusable analytical frameworks and methodologies, and help shape the technical direction of Huron's DSML capabilities.# Required Qualifications 5+ years of hands-on experience conducting data science and advanced analytics -not just ad-hoc analysis, but structured analytical projects that drove business decisions. You've framed problems, developed hypotheses, analyzed data, and delivered insights that created measurable impact. Experience leading and developing technical teams -including coaching, mentorship, methodology review, and performance management. Demonstrated ability to build high-performing teams and develop junior talent. Strong Python and SQL programming skills with deep experience in the data science ecosystem (Pandas, NumPy, Scikit-learn, statsmodels, visualization libraries). Comfortable writing production-quality code, not just notebooks. Solid foundation in statistics and machine learning : hypothesis testing, regression analysis, classification, clustering, experimental design, causal inference, and understanding of when different approaches are appropriate for different questions. Experience with deep learning and modern neural architectures -understanding of transformer models, embeddings, transfer learning, and how to leverage foundation models for analytical tasks. You know when ML approaches add value over classical methods, and how to integrate them into rigorous analytical workflows. Proficiency with data platforms : Microsoft Fabric, Snowflake, Databricks, or similar cloud analytics environments. You're comfortable working with large datasets and can optimize queries for performance. Exceptional communication and data storytelling skills -ability to distill complex analyses into clear narratives, create compelling visualizations, lead client meetings, and build trusted relationships with executive audiences. This is non-negotiable. Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field (or equivalent practical experience). Flexibility to work in a hybrid model with periodic travel to client sites as needed.# Preferred Qualifications Experience in Financial Services, Manufacturing, or Energy & Utilities industries. Background in experimental design, A/B testing, and causal inference methodologies-including propensity score matching, difference-in-differences, or instrumental variables. Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and neural architectures-including transformers, attention mechanisms, and fine-tuning pretrained models for NLP, time-series, or tabular data applications. Experience building AI-assisted analytical workflows-leveraging foundation model APIs, vector databases, and retrieval systems to accelerate insight extraction from unstructured data. Experience with Bayesian methods, probabilistic programming (PyMC, NumPyro, etc.), or uncertainty quantification in business contexts. Strong visualization and data interface design and development skills using programmatic visualization libraries (Plotly, Altair, D3). Proficiency with AI-assisted rapid data application development using Cursor, Lovable, v0, etc. Experience with time-series analysis, forecasting methods (ARIMA, Prophet, neural forecasting), and demand planning applications. Cloud certifications (Azure Data Scientist, Databricks ML Associate, AWS ML Specialty). Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new
Data Science Manager page is loaded Data Science Managerremote type: Hybridlocations: Belfast - 20 Adelaide Streetposted on: Posted Todayjob requisition id: JR-Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future. Join our team as the expert you are now and create your future. Data Science Manager We're seeking a Data Science Manager to join the Data Science & Machine Learning team in our Commercial Digital practice, where you'll lead advanced analytics initiatives that transform how Fortune 500 companies make decisions across Financial Services, Manufacturing, Energy & Utilities, and other commercial industries.Managers play a vibrant, integral role at Huron. Their invaluable knowledge reflects in the projects they manage and the teams they lead. Known for building long-standing partnerships with clients, they collaborate with colleagues to solve their most important challenges. Our Managers also spend significant time mentoring junior staff on the engagement team-sharing expertise, feedback, and encouragement. This promotes a culture of respect, unity, collaboration, and personal achievement.This isn't a reporting role or a dashboard factory-you'll own the full analytics lifecycle from hypothesis formulation through insight delivery, while leading and developing a team of data scientists and analysts. You'll work on problems that matter: experimental designs that validate multi-million-dollar strategies, predictive models that surface hidden patterns in complex data, and deep learning pipelines that extract signal from unstructured text, images, and time-series. Our clients are Fortune 500 companies looking for partners who can find the signal in the noise and tell the story that drives action.The variety is real. In your first year, you might lead a customer segmentation and lifetime value analysis for a financial services firm, design and analyze a pricing experiment for a global manufacturer, and build an agentic anomaly detection system for a utility company's operational data-all while developing the next generation of data science talent at Huron. If you thrive on rigorous analysis, clear communication of complex findings, and building high-performing teams, this role is for you.# What You'll Do Lead and mentor junior data scientists and analysts -provide technical guidance, review analytical approaches and code, and support professional development. Foster a culture of intellectual curiosity, rigorous methodology, and clear communication within the team. Manage complex multi-workstream analytics projects -oversee project planning, resource allocation, and delivery timelines. Ensure analyses meet quality standards and client expectations while maintaining methodological rigor. Design and execute end-to-end data science workflows -from problem framing and hypothesis development through exploratory analysis, modeling, validation, and insight delivery. Own the analytical approach and ensure conclusions are defensible. Lead development of both traditional statistical and modern AI-powered analyses -including regression, classification, clustering, causal inference, A/B testing, and modern deep learning approaches using embeddings, transformer architectures, and foundation models for text, time-series, and multimodal analysis. Build predictive and prescriptive models that drive business decisions-customer segmentation, churn prediction, demand forecasting, pricing optimization, risk scoring, and operational efficiency analysis for commercial enterprises. Translate complex analytical findings into actionable insights -create compelling data narratives, develop executive-ready presentations, and communicate technical results to non-technical stakeholders in ways that drive decisions. Serve as a trusted advisor to clients -build long-standing partnerships, deeply understand business problems, formulate the right analytical questions, and deliver insights that create measurable value. Contribute to practice development -participate in business development activities, develop reusable analytical frameworks and methodologies, and help shape the technical direction of Huron's DSML capabilities.# Required Qualifications 5+ years of hands-on experience conducting data science and advanced analytics -not just ad-hoc analysis, but structured analytical projects that drove business decisions. You've framed problems, developed hypotheses, analyzed data, and delivered insights that created measurable impact. Experience leading and developing technical teams -including coaching, mentorship, methodology review, and performance management. Demonstrated ability to build high-performing teams and develop junior talent. Strong Python and SQL programming skills with deep experience in the data science ecosystem (Pandas, NumPy, Scikit-learn, statsmodels, visualization libraries). Comfortable writing production-quality code, not just notebooks. Solid foundation in statistics and machine learning : hypothesis testing, regression analysis, classification, clustering, experimental design, causal inference, and understanding of when different approaches are appropriate for different questions. Experience with deep learning and modern neural architectures -understanding of transformer models, embeddings, transfer learning, and how to leverage foundation models for analytical tasks. You know when ML approaches add value over classical methods, and how to integrate them into rigorous analytical workflows. Proficiency with data platforms : Microsoft Fabric, Snowflake, Databricks, or similar cloud analytics environments. You're comfortable working with large datasets and can optimize queries for performance. Exceptional communication and data storytelling skills -ability to distill complex analyses into clear narratives, create compelling visualizations, lead client meetings, and build trusted relationships with executive audiences. This is non-negotiable. Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field (or equivalent practical experience). Flexibility to work in a hybrid model with periodic travel to client sites as needed.# Preferred Qualifications Experience in Financial Services, Manufacturing, or Energy & Utilities industries. Background in experimental design, A/B testing, and causal inference methodologies-including propensity score matching, difference-in-differences, or instrumental variables. Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and neural architectures-including transformers, attention mechanisms, and fine-tuning pretrained models for NLP, time-series, or tabular data applications. Experience building AI-assisted analytical workflows-leveraging foundation model APIs, vector databases, and retrieval systems to accelerate insight extraction from unstructured data. Experience with Bayesian methods, probabilistic programming (PyMC, NumPyro, etc.), or uncertainty quantification in business contexts. Strong visualization and data interface design and development skills using programmatic visualization libraries (Plotly, Altair, D3). Proficiency with AI-assisted rapid data application development using Cursor, Lovable, v0, etc. Experience with time-series analysis, forecasting methods (ARIMA, Prophet, neural forecasting), and demand planning applications. Cloud certifications (Azure Data Scientist, Databricks ML Associate, AWS ML Specialty). Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new
