Data Science Consultant with Financial Services Expertise

As one of the world's leading digital transformation service providers, we are looking to enhance our Data Practice across Europe to meet the increasing client demand for our Data Science and AI services. We are seeking a highly skilled and experienced Data Science Consultant to join our team.
The ideal candidate will have a strong background in data science, analytics, IT consulting, and domain expertise in financial services. As a Data Science Consultant, you will work closely with clients to understand their business challenges, design and implement data-driven solutions, and provide actionable insights that drive business value. Your ability to address challenges specific to financial services, such as risk modeling, fraud detection, and regulatory compliance, will be a critical asset.

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• Support financial services clients with the definition and implementation of their AI strategy, focusing on areas such as risk management, customer analytics and operational efficiency
• Implement and oversee AI governance frameworks, with an emphasis on regulatory compliance (e.g., Basel III, GDPR) and ethical AI principles
• Ideate, design and implement AI-enabled solutions for financial services use cases, such as credit scoring, fraud detection, customer segmentation and predictive modeling
• Lead the process of taking AI/ML models from development to production, ensuring robust MLOps practices tailored to financial data environments
• Monitor and manage model performance, including addressing issues related to explainability, data drift and model drift in financial models
• Collaborate with risk, compliance and legal teams to navigate financial regulations and ensure models meet stringent industry standards
• Engage with senior executives, effectively communicating AI opportunities, risks and strategies in accessible terms, particularly in the financial services context
• Maintain up-to-date knowledge of industry trends, emerging technologies and regulatory changes impacting AI/ML in financial services
• Support pre-sales activities, including client presentations, demos and RFP/RFI responses tailored to financial services prospects

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Finance, Economics or a related field
• 5+ years of experience in data science, analytics or related roles within the financial services industry or IT consulting for financial institutions
• Strong communication skills, comfortable presenting to senior business leaders in banking, insurance or investment firms
• Proven experience in financial services data science projects, such as credit risk modeling, anti-money laundering (AML) systems or algorithmic trading models
• Familiarity with key financial industry regulations, such as Basel III, Solvency II, MiFID II or the EU AI regulatory framework
• Deep understanding of LLMs and their application in areas like financial document analysis, customer service chatbots or regulatory reporting
• Expertise in fraud detection techniques, anomaly detection and compliance analytics
• Strong understanding of ML Ops principles and experience in deploying and managing AI/ML models in financial systems
• Proficiency in Python and familiarity with AI/ML tools and platforms such as Azure, AWS, GCP, Databricks, MLFlow, Airflow and financial-specific platforms like Bloomberg Terminal, SAS, or MATLAB
• Experience with structured and unstructured financial data, including time-series analysis, market data and transactional data
• Ability to articulate complex AI risks and strategies to non-technical stakeholders, including senior executives in banking and insurance

• Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Finance, Economics or a related field
• Expertise in stress testing models, scenario analysis and portfolio optimization

• EPAM Employee Stock Purchase Plan (ESPP)
• Protection benefits including life assurance, income protection and critical illness cover
• Private medical insurance and dental care
• Employee Assistance Program
• Competitive group pension plan
• Cyclescheme, Techscheme and season ticket loans
• Various perks such as free Wednesday lunch in-office, on-site massages and regular social events
• Learning and development opportunities including in-house training and coaching, professional certifications, over 22,000 courses on LinkedIn Learning Solutions and much more
• If otherwise eligible, participation in the discretionary annual bonus program
• If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program
• *All benefits and perks are subject to certain eligibility requirements