Senior Data Scientist - Scientific AI, Life Sciences

McKinsey & Company, Inc.; London; On-site; GBP 70,000 - 110,000; Full time

Job summary

An established industry player is seeking a Senior Data Scientist to join their London office. This role involves working with cutting-edge AI teams to develop innovative models and insights in the life sciences sector. You will leverage your expertise in machine learning and statistics to tackle complex client challenges and contribute to the firm's scientific AI offerings. Collaborating with a multidisciplinary team, you will ensure the statistical validity of analytics and help shape the future of AI applications in therapeutics and materials. If you are passionate about driving impactful solutions through advanced analytics, this is the perfect opportunity for you.

Qualifications

• 5+ years experience in statistics or mathematics with a focus on research.
• Strong programming skills in Python and experience with analytics libraries.

Responsibilities

• Develop AI and machine learning models for client delivery.
• Translate complex technical methods for non-technical stakeholders.

Skills

Machine Learning

Statistical Analysis

Python Programming

Client Delivery

Data Visualization

Education

Master’s degree in Statistics, Mathematics, or Computer Science

PhD in relevant field

Tools

GitHub

Pandas

NumPy

Matplotlib

Scikit-learn

PyTorch

TensorFlow

Job description

Your Growth

You will be working in our 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 Senior 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.

Your Impact

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 Senior 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.

Your qualifications and skills

• Master’s degree with 5+ years or PhD degree with 2+ years of relevant experience in statistics, mathematics, computer science, or equivalent experience with experience in research
• Experience in client delivery with direct client contact
• 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