Senior Data Scientist | Banking Experience Mandatory

Location: United Kingdom Contract duration: 1 year (extension possible) Start Date: ASAP Experience: 8+ years Salary: TBN Visa Sponsorship: Available if needed Key Accountabilities Machine Learning Model Development • Design and develop machine learning models for pricing optimization, including dynamic pricing, rate optimization, and fee structures • Build propensity models for customer behavior prediction, including churn, cross-sell, upsell, and product adoption • Develop recommendation systems for personalized product offerings, next-best-action, and customer engagement Banking Domain Application • Apply deep banking domain knowledge to frame business problems as machine learning solutions with measurable outcomes • Partner with Risk, Finance, and business units to identify high-value modelling opportunities • Ensure models incorporate relevant regulatory requirements, risk considerations, and business constraints Analysis & Insights • Conduct exploratory data analysis to identify patterns, relationships, and modelling opportunities in banking data • Translate model outputs into actionable business recommendations and insights • Develop model performance metrics aligned with business KPIs and financial outcomes • Create data visualizations and reports for stakeholder communication Prototyping & Delivery • Develop working prototypes in Python demonstrating model functionality and business value • Create clear documentation of model methodology, assumptions, limitations, and use cases • Collaborate with ML Engineers and AI Engineers to transition prototypes into production systems Stakeholder Collaboration & Governance • Partner with business stakeholders to understand requirements and validate model outputs • Present model results, methodology, and recommendations to senior management • Contribute to model governance, validation, and documentation requirements • Ensure compliance with data policies, ethical standards, and regulatory requirements Key Competencies Machine Learning & Statistics • Expert knowledge of supervised and unsupervised learning techniques for classification, regression, and clustering • Deep experience with pricing models, propensity modelling, and recommendation systems • Strong foundation in statistical analysis, hypothesis testing, and experimental design • Familiarity with deep learning frameworks such as TensorFlow and PyTorch Banking Domain Expertise • Comprehensive understanding of banking products (Retail or Corporate), services, and customer lifecycle • Knowledge of Risk functions, including credit risk, market risk, and operational risk frameworks • Understanding of Finance functions, including P&L drivers, cost allocation, and profitability analysis • Familiarity with regulatory requirements impacting model development (e.g., IFRS 9, Basel) Technical Skills • Python for data analysis and model development (pandas, scikit-learn, XGBoost, etc.) • Advanced SQL skills, including stored procedures, window functions, temporary tables, and recursive queries • Experience with data visualization and reporting tools • Familiarity with Git (GitHub/GitLab) for version control • Basic understanding of Spark for large-scale data processing • Awareness of MLOps practices and model deployment concepts (MLflow, TFX) Communication & Collaboration • Ability to translate complex analytical concepts into business language for non-technical stakeholders • Strong executive-level presentation skills • Experience working with cross-functional business and technology teams • Experience with Agile methodologies (Kanban, Scrum) Qualifications & Experience • Master’s degree or PhD in Finance, Economics, Statistics, Mathematics, or a quantitative field (strongly preferred) • 8+ years of experience in data science or quantitative analysis roles • Minimum 5 years of experience in the banking or financial services industry (mandatory) • Proven track record of delivering ML models in pricing, propensity, or recommendation domains • Background in Risk, Finance, or quantitative banking functions preferred • Experience with model validation, governance, and regulatory requirements in financial services • Professional certifications in Risk (FRM, PRM) or Finance (CFA) are a plus