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Data Science Consultant - Life Sciences

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Hybrid

Data Science Consultant - Life Sciences

EPAM Systems

Data Science Consultant - Life Sciences

Skills

Google Cloud PlatformSQL QueriesBig DataDeep LearningPythonData SciencePyTorchTensorFlowDatabricksMachine LearningAIAWSNLP / Natural Language ProcessingAzure

2 months ago

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Important information


Location:

London, UK

Work mode:

Hybrid

Published on:

19 August 2026

What they need


We're looking for a Data Science Consultant – Life Sciences to join our team in London, UK in a hybrid working mode.

In this role, you will help leading pharmaceutical and life sciences organizations leverage data, AI and advanced analytics to enable transformation across R&D, clinical, and commercial functions. Acting as a trusted advisor, you will design and deliver scalable solutions using machine learning, Generative AI and large language models to address key challenges in drug discovery, clinical development, pharmacovigilance and patient engagement.

You will combine domain experience with technical expertise and consulting capabilities, working closely with senior stakeholders to align AI strategies to business priorities. This is an opportunity to drive measurable value and shape the future of AI adoption in life sciences.

Responsibilities

  • Design and implement AI-driven solutions across life sciences use cases such as drug discovery, clinical trial optimization and pharmacovigilance
  • Advise executive stakeholders on AI strategy and translate technical concepts into actionable business outcomes
  • Define and deliver enterprise-wide AI and machine learning adoption roadmaps aligned to business objectives
  • Create governance frameworks to ensure AI solutions meet regulatory and ethical requirements (e.g., GDPR, FDA, EMA)
  • Prototype Generative AI and LLM-based applications to support literature mining, safety monitoring and patient programs
  • Collaborate with data engineers, clinicians and business teams to tailor solutions to client needs
  • Deploy AI and machine learning models in production environments using established MLOps and LLMOps practices
  • Use cloud platforms and data solutions to ensure scalability and operational integrity
  • Present data-driven recommendations to senior audiences, demonstrating the impact of AI solutions
  • Support pre-sales activities including solutioning, proposals, workshops and industry presentations

Requirements

  • 8+ years of experience in data science with a focus on life sciences projects, ideally in consulting or enterprise settings
  • Practical experience delivering production-grade AI and machine learning solutions in regulated environments
  • Hands-on knowledge of Generative AI, LLM application and their relevance to life sciences use cases
  • Expertise in structured and unstructured life sciences data, including clinical and real-world datasets
  • Familiarity with machine learning techniques such as NLP and deep learning, applied to biomedical data
  • Knowledge of cloud technologies (Azure, AWS or GCP) and model deployment using MLOps frameworks
  • Strong programming skills in Python and SQL with experience in frameworks such as PyTorch, TensorFlow and Hugging Face
  • Experience using data platforms and big data frameworks like Databricks and Spark
  • Excellent communication skills for engaging C-level stakeholders and aligning technical outcomes with business value

Nice to have

  • Experience applying AI in drug discovery, safety monitoring or clinical development contexts
  • Understanding of biomedical ontologies or knowledge graph applications
  • Knowledge of regulatory frameworks (FDA, EMA) and experience with data privacy considerations
  • Background in computational biology, biostatistics or related scientific discipline
  • Familiarity with federated learning concepts or privacy-preserving machine learning techniques

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, and courses
  • 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

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