Data Scientist

Contract duration:1 year (extension possible)Start Date:ASAPExperience:8+ yearsVisa Sponsorship:Available if neededKey Accountabilities 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 engagementBanking 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 constraintsAnalysis & Insights Conduct exploratory data analysis to identify patterns, relationships, and modelling opportunities in banking data Translate model outputs into, A global financial institution in Greater London is seeking a Lead Machine Learning Scientist to spearhead the development of cutting-edge AI solutions. The role involves leading teams to build machine learning models, mentoring junior staff, and collaborating across...

actionable business recommendations and insights Develop model performance metrics aligned with business KPIs and financial outcomes Create data visualizations and reports for stakeholder communicationPrototyping & 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 systemsStakeholder 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 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 PyTorchBanking 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) Ability to translate complex analytical concepts into business language for non-technical stakeholders 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#J-18808-Ljbffr Similar jobs, Job Description Senior Data Analyst/Scientist - Power BI - sought by investment bank based in London - Contract - Hybrid inside IR35 - umbrella Essential: - Proven experience in a Data Analysis or Science - Strong understanding of front-office trading, risk, or market...

£50 per hour

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Direct message the job poster from AryaXAI Interpreting and Aligning AI for mission-critical use cases AryaXAI stands at the forefront of AI innovation, revolutionizing how AI is applied in mission-critical, highly regulated industries by building explainable, safe, and..., Shift is the leading AI platform for insurance. Shift combines generative, agentic, and predictive AI to transform underwriting, claims, and fraud and risk - driving operational efficiency, exceptional customer experiences and measurable business impact. Trusted by the..., A leading financial services company in the United Kingdom is looking for a Machine Learning Specialist with over 8 years of experience. The role involves designing innovative machine learning models for pricing optimization in banking. Ideal candidates have advanced...