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For Companies At a Glance
- Tasks: Develop AI models, support client discussions, and create cutting-edge knowledge in life sciences.
- Company: Join a global firm known for its diverse community and commitment to innovation.
- Benefits: Enjoy competitive salary, comprehensive health coverage, and a culture of continuous learning.
- Why this job: Make a real impact with your ideas while growing in a supportive, high-performance environment.
- Qualifications: Master’s or PhD with 2+ years in statistics or computer science; strong programming skills required.
- Other info: Work in London with a multi-disciplinary team on groundbreaking AI projects.
The predicted salary is between 36000 - 60000 £ per year.
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 will 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 will 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. 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 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 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 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.
Your qualifications and skills
- 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
Data Scientist - Scientific AI, Life Sciences employer: McKinsey & Company, Inc.
Contact Detail:
McKinsey & Company, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Scientific AI, Life Sciences
✨Tip Number 1
Familiarise yourself with the specific AI and machine learning techniques mentioned in the job description, such as Bayesian statistics and deep learning. Being able to discuss these topics confidently during interviews will demonstrate your expertise and enthusiasm for the role.
✨Tip Number 2
Network with current or former employees of StudySmarter or similar companies. Engaging in conversations about their experiences can provide valuable insights into the company culture and expectations, which you can leverage during your application process.
✨Tip Number 3
Prepare to showcase your problem-solving skills by discussing past projects where you've applied machine learning techniques. Be ready to explain how you translated complex technical concepts to non-technical stakeholders, as this is a key requirement for the role.
✨Tip Number 4
Stay updated on the latest trends and advancements in AI and life sciences. Being knowledgeable about recent developments can help you engage in meaningful discussions during interviews and show your commitment to continuous learning, which aligns with our values at StudySmarter.
We think you need these skills to ace Data Scientist - Scientific AI, Life Sciences
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in statistics, mathematics, and machine learning. Emphasise any projects or roles where you've applied these skills, particularly in a life sciences context.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and AI, and how it relates to the life sciences. Mention specific examples of how you've solved complex problems using machine learning techniques and your ability to communicate technical concepts to non-technical stakeholders.
Showcase Your Technical Skills: Include a section in your application that lists your programming skills, particularly in Python and relevant libraries. If you have experience with version control systems like GitHub, make sure to mention that as well.
Highlight Continuous Learning: Demonstrate your commitment to continuous learning by mentioning any recent courses, certifications, or projects that showcase your growth in data science and AI. This aligns with the company's emphasis on development and mentorship.
How to prepare for a job interview at McKinsey & Company, Inc.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning techniques and programming languages, especially Python. Bring examples of projects where you've applied these skills to solve real-world problems, as this will demonstrate your capability to translate complex technical methods into practical solutions.
✨Emphasise Your Resilience
Given the high-performance culture described, it's important to convey your resilience and determination. Share specific instances where you faced challenges in your work and how you overcame them. This will show that you thrive in demanding environments and are willing to learn from setbacks.
✨Prepare for Collaborative Scenarios
Since the role involves working in multi-disciplinary teams, be ready to discuss your experiences collaborating with diverse groups. Highlight how you value different perspectives and how this has led to innovative solutions in your past projects.
✨Articulate Your Learning Journey
The company values continuous learning, so be sure to talk about how you actively seek feedback and use it to improve your skills. Discuss any structured learning programs or mentorship experiences you've had, and how they have shaped your professional development.
