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Data Scientist - Scientific AI, Life Sciences

McKinsey & Company, Inc.

Greater London

On-site

GBP 55,000 - 85,000

Full time

Today
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Job summary

A global consulting firm is seeking a Data Scientist in their London office to develop AI and machine learning models for life sciences. The ideal candidate will have a Master’s or PhD degree and over 2 years of experience in statistics or mathematics. You'll collaborate with multi-disciplinary teams, driving innovation in AI for therapeutic and materials challenges. The role requires strong programming skills, particularly in Python, and proficiency with relevant analytics libraries, ensuring impactful client solutions and insights.

Benefits

Competitive salary
Comprehensive benefits package
Learning and development opportunities

Qualifications

  • Master’s or PhD degree in a relevant field.
  • 2+ years of experience in statistics, mathematics, or equivalent experience.
  • Proven experience applying machine learning techniques.

Responsibilities

  • Developing AI and machine learning models & pipelines.
  • Supporting client discussions and prototype development.
  • Translating results for senior stakeholders.

Skills

Statistics
Mathematics
Machine Learning
Python
Causality
Bayesian Statistics
Version Control (GitHub)
Deep Learning

Education

Master’s or PhD degree

Tools

Pandas
NumPy
Matplotlib
Scikit-learn
PyTorch/TensorFlow/Keras
Job description
Your Growth

Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.

In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.

When you join us, you will have:

  • Continuous learning:Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
  • A voice that matters:From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
  • Global community:With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
  • World‑class benefits:On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well‑being for you and your family.
Your Impact

As a Data Scientist in our Life Sciences practice, you will play a pivotal role in the creation/dissemination of cutting‑edge knowledge and proprietary assets. Your role will be split between developing new internal knowledge, building AI and machine learning models & pipelines, supporting client discussions, prototype development, and deploying directly with client delivery teams.

You will be on McKinsey’s global scientific AI team helping to answer industry questions related to how AI can be used for therapeutics, chemicals & materials (including small molecules, proteins, mRNA, polymers, etc.). You will work in a multi‑disciplinary team and build the firm’s reputation in your area of expertise. You will work with cutting edge AI teams on research and development topics across our life sciences, global energy and materials (GEM), and advanced industries (AI) practices, serving as a data scientist in a technology development and delivery capacity.

As part of our London office, you will use your expertise in advanced mathematics, statistics, and/or machine learning, to help build and shape McKinsey’s scientific AI offering. You will bring distinctive statistical, machine learning, and AI competency to complex client problems.

In this role you will support the manager of data science with the development of data science and analytics roadmap of assets across cell‑level initiatives. You will deliver distinctive capabilities, models, and insights through your work with client teams and clients.

You will ensure statistical validity and outputs of analytics, AI/ML models and translate results for senior stakeholders, and will write optimized code to advance our Data Science Toolbox and codify analytical methodologies for future deployment.

Your qualifications and skills
  • Master’s or PhD degree
  • 2+ years of relevant experience in statistics, mathematics, computer science, or equivalent experience with experience in research
  • Proven experience applying machine learning techniques to solve business problems
  • Proven experience in translating technical methods to non‑technical stakeholders
  • Strong programming experience in python (R, Python, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit‑learn, statsmodels, pymc, pytorch/tf/keras, langchain)
  • Experience with version control (GitHub)
  • ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate models, transformers, Knowledge Graphs, Agents, Graph NNs, Deep Learning, computer vision
  • Ability to write production code and object‑oriented programming
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