Data Scientist - Life Sciences

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:

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• 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. 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, which includes medical, dental, mental health, and vision coverage for you, your spouse/partner, and children.
  

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 bring distinctive statistical, machine learning, and AI competency to complex client problems.

With your expertise in advanced mathematics, statistics, and/or machine learning, you will help build and shape McKinsey’s scientific AI offering.

As a Data Scientist, you will play a pivotal role in the creation/dissemination of cutting-edge knowledge and proprietary assets.

You will work in a multi-disciplinary team and build the firm’s reputation in your area of expertise.

You will ensure statistical validity and outputs of analytics, AI/ML models and translate results for senior stakeholders.

You will write optimized code to advance our Data Science Toolbox and codify analytical methodologies for future deployment.

You will be working in the London office in our Life Sciences practice.

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.

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.).

In this role you will support the manager of data science on 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.

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• Master’s or PhD degree with 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