Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead/Senior Data Scientist

EPAM
City of London
2 days ago
Create job alert

This job is brought to you by Jobs/Redefined, the UK's leading over-50s age inclusive jobs board.


Are you passionate about Data Science and Artificial Intelligence? Do you thrive at the intersection of technical innovation and business strategy, finding satisfaction in translating complex ideas into scalable client-centric solutions? If so, we have an exciting opportunity for you.


As a Senior/Lead Data Scientist, you will play a pivotal role in driving the development and deployment of state-of-the-art AI models and data-driven solutions that deliver measurable impact. You'll move beyond building prototypes to deploying robust production-grade systems. We are looking for an experienced applied data scientist who can combine exceptional technical skills with strategic foresight and the ability to partner effectively with business and technical teams. You'll have proven expertise in managing project timelines and delivering results that align with organizational goals while fostering collaboration and innovation within the team.


Responsibilities

  • Build innovative machine learning and AI solutions designed to address a variety of business challenges and opportunities
  • Continuously tune and refine models for improved performance, accuracy, scalability and reliability across multiple use cases
  • Establish frameworks to assess accuracy, performance metrics and data fitness to ensure models meet real-world demands
  • Lead efforts to standardize model evaluation, coding practices and data science workflows to uphold high-quality production-level code
  • Work closely with business stakeholders to define project goals and technical requirements while partnering with data engineering teams to streamline development roadmaps
  • Bring cutting-edge techniques like NLP, Large Language Models (LLMs) and Generative AI (GenAI) to solve real-world problems with demonstrable results

Qualifications

  • Extensive experience applying data science methods including knowledge of NLP, Large Language Models (LLMs) and Generative AI technologies
  • Expertise in object-oriented programming with deep knowledge of critical machine learning libraries (e.g. TensorFlow, PyTorch, scikit-learn) and best practices for efficient coding
  • A solid grasp of probability, inference and robust data analysis techniques to inform model selection, development and accurate interpretation of outputs
  • Proven ability to take AI models from ideation through deployment ensuring scalability, reliability and alignment with business objectives
  • Hands-on experience with cloud platforms (Azure and/or AWS) and deployment pipelines to deliver scalable production-ready solutions
  • Skilled at establishing, maintaining and advocating for clean, maintainable and well-documented code across projects
  • Ability to work effectively with both technical and non-technical stakeholders bridging the gap between business needs and development execution
  • Adept at translating complex technical ideas into clear actionable insights for teammates, executives and clients

Benefits

  • 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

Lead/Senior Data Scientist

Lead/Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

LLM / NLP Data Scientist Lead - Vice President - ESG

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.