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For Companies At a Glance
- Tasks: Develop AI models and support client discussions in life sciences.
- Company: Join a global leader in scientific AI with a diverse team.
- Benefits: Competitive salary, comprehensive benefits, and a focus on well-being.
- Why this job: Make a real impact in life sciences while growing your skills rapidly.
- Qualifications: Master’s or PhD with experience in machine learning and programming.
- Other info: Dynamic environment with mentorship and global collaboration opportunities.
The predicted salary is between 36000 - 60000 ÂŁ 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, 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
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
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common data science questions and case studies. We recommend simulating real interview scenarios with friends or mentors to build your confidence and refine your answers.
✨Tip Number 3
Showcase your skills through projects! Create a portfolio of your work, including any AI models or analyses you've developed. This not only demonstrates your expertise but also gives you something tangible to discuss during interviews.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Scientist - Scientific AI, Life Sciences
Some tips for your application 🫡
Show Your Passion for Data Science: When writing your application, let your enthusiasm for data science shine through! Share specific examples of projects or experiences that sparked your interest in AI and machine learning, especially in the life sciences field. We want to see your drive and curiosity!
Tailor Your Application: Make sure to customise your application to highlight how your skills align with the role. Use keywords from the job description, like 'machine learning' and 'statistics', to demonstrate that you understand what we're looking for. This helps us see you as a perfect fit!
Be Clear and Concise: Keep your writing clear and to the point. Avoid jargon unless it's necessary, and make sure your ideas flow logically. We appreciate well-structured applications that are easy to read, so take the time to proofread and polish your work before hitting send!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you're proactive and keen to join our team at StudySmarter!
How to prepare for a job interview at Mckinsey & Company, Inc.
✨Know Your Stuff
Make sure you brush up on your statistics, machine learning techniques, and programming skills, especially in Python. Be ready to discuss specific projects where you've applied these skills, as well as the outcomes. This will show that you not only understand the theory but can also apply it practically.
✨Show Your Resilience
Since the role requires someone who thrives in a high-performance culture, be prepared to share examples of challenges you've faced in previous roles. Talk about how you picked yourself up after setbacks and what you learned from those experiences. This demonstrates your determination and growth mindset.
✨Communicate Clearly
You'll need to translate complex technical concepts to non-technical stakeholders, so practice explaining your work in simple terms. Use analogies or real-world examples to make your points relatable. This will highlight your ability to communicate effectively within a multi-disciplinary team.
✨Embrace Feedback
During the interview, show that you're open to feedback and eager to learn. Discuss how you've used feedback in the past to improve your work or approach. This aligns with the company's culture of continuous learning and will demonstrate that you're a good fit for their environment.
