Principal Data Science Consultant - Financial Services Expertise

EPAM
London
1 day ago
Create job alert

As one of the worlds 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 experiencedData Science Consultantto 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.

Responsibilities

  • 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.

Requirements

  • Bachelors or Masters 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.

Nice to have

  • 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.

We offer

  • 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.

J-18808-Ljbffr

Related Jobs

View all jobs

Principal Data Science Consultant - Gen AI Specialist

Senior / Principal Recruitment Consultants - Data / Technology Perm & Interim

Senior Operational Analyst Consultant

Operational Analyst Consultant

Principal Statistician - FSP

LUPUS Clinical Research Fellow

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.

Data Science Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Data science has become a linchpin in modern business, transforming oceans of raw data into actionable insights that guide strategy, product development, and personalised customer experiences. With this surge in data-centric operations, the need for effective data science leadership has never been more critical. Guiding a team of data scientists, analysts, and machine learning engineers requires not only technical acumen but also the ability to foster collaboration, champion ethical practices, and align complex modelling efforts with overarching business goals. This article provides practical guidance for managers and aspiring leaders aiming to excel in data-driven environments. By exploring strategies to motivate data science professionals, develop mentoring frameworks, and set achievable milestones, you will be better prepared to steer your team towards meaningful, evidence-based outcomes.

10 Essential Books to Read to Nail Your Data Science Career in the UK

Data science continues to be one of the most exciting and rapidly evolving fields in tech. With industries across the UK—ranging from finance and healthcare to e-commerce and government—embracing data-driven decision-making, the demand for skilled data scientists has soared. Whether you're a recent graduate looking for your first role or a professional aiming to advance your career, staying updated through books is crucial. In this article, we explore ten essential books every data science job seeker in the UK should read. Each book provides valuable insights into core concepts, practical applications, and industry-standard tools, helping you build skills employers are actively looking for.