As Data Science Manager, you will lead a small, high performing team delivering the models, analytics and insight that shape Onmo's credit, commercial and customer strategies. You'll own the data science roadmap, drive the development and governance of predictive models, and ensure our work advances business goals, regulatory expectations and great customer outcomes under the FCA Consumer Duty.
Example Strategic Initiatives:
Early intervention models for vulnerable and at risk customers.
Enhancements to risk and growth models across the lifecycle.
Utilisation and engagement forecasting to unlock responsible growth.
Behaviour scorecards and feature engineering (including Open Banking).
Champion-challenger testbeds and a model governance library.
Leadership & Roadmap: Set direction, prioritise impact and create clear ways of working for a high performing team.
Model Development & Governance: Build, validate and document robust predictive models; ensure compliance with model governance, FCA guidelines and Onmo standards.
Model Monitoring: Establish champion-challenger frameworks and performance dashboards; escalate and remediate drift proactively.
Analytics & Experimentation: Design and run tests that unlock growth, improve risk selection and enhance customer experience.
Credit Risk & Decisioning: Partner with Risk, Product and Engineering to embed models across the lifecycle (acquisition, utilisation, behaviour, collections).
Cross functional Collaboration: Translate complex analysis for non technical stakeholders and influence decisions across the business.
At Onmo we all take collective responsibility for our individual roles in creating the best outcomes for our customers. In this role that involves;
Following the FCA Conduct Rules;
You must act with integrity
You must act with due skill, care and diligence
You must be open and cooperative with the FCA, PRA and other regulators
You must pay due regard to the interests of customers and treat them fairly
You must observe proper standards of market conduct
Clear, motivating leadership style with a bias for execution and structured delivery.
Excellent written documentation and stakeholder communication.
Pragmatic, automation minded and curious; you value simplicity and standards.
Strategic thinker who enjoys solving ambiguous problems in a fast paced fintech.
Essential Qualifications/Experiencel:
4+ years in Data Science (or similar analytics) with delivery in financial services and/or credit risk.
People leadership: mentoring, coaching and representing Data Science with senior stakeholders.
Model development expertise (e.g., logistic regression, gradient boosted trees such as XGBoost).
Production grade Python: clean, modular code; comfortable building production pipelines.
Model governance: monitoring, documentation standards and controls aligned to FCA expectations and Consumer Duty.
Advanced SQL and data manipulation to turn raw data into actionable insight.
Engineering best practice: Git, Docker and CI/CD.
Communication & influence: explain complex topics simply and advocate for data driven decisions.
Visualisation tools (Power BI, Tableau) and analytics platforms (Databricks).
Scale up experience; comfortable with pace and ambiguity.
LLMs/GenAI awareness and practical judgment on value adding use cases