At a Glance
- Tasks: Develop AI models, support client discussions, and ensure statistical validity in analytics.
- 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 in relevant fields with experience in machine learning and client delivery.
- Other info: Work in London with cutting-edge AI teams on life sciences and advanced industries.
The predicted salary is between 48000 - 72000 £ 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 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. 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 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
Senior 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 Senior Data Scientist - Scientific AI, Life Sciences
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning, particularly in the life sciences sector. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field by attending relevant conferences or webinars. Engaging with others can provide insights into the company culture and may even lead to referrals, which can significantly boost your chances of landing the job.
✨Tip Number 3
Prepare to discuss your past projects in detail, especially those that involved client delivery and translating complex data into actionable insights. Being able to articulate your experience clearly will demonstrate your value to potential employers.
✨Tip Number 4
Showcase your programming skills by contributing to open-source projects or creating your own projects on platforms like GitHub. This not only enhances your coding abilities but also provides tangible evidence of your expertise to share during interviews.
We think you need these skills to ace Senior 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 direct client delivery experience and your ability to translate technical methods to non-technical stakeholders.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and life sciences. Discuss how your background aligns with the role and mention specific projects or experiences that demonstrate your skills in developing AI models and working in multi-disciplinary teams.
Showcase Technical Skills: Clearly outline your programming experience, particularly in Python and relevant analytics libraries. Include any experience with version control systems like GitHub and highlight specific machine learning techniques you have applied in past roles.
Demonstrate Continuous Learning: Mention any ongoing education or training related to data science and AI. This could include courses, certifications, or participation in relevant workshops that showcase your commitment to professional growth and staying updated with industry trends.
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 handle the technical demands of the role.
✨Communicate Clearly with Non-Technical Stakeholders
Since the role involves translating complex technical methods to non-technical stakeholders, practice explaining your past projects in simple terms. This will show your ability to bridge the gap between technical and non-technical teams, which is crucial for success in this position.
✨Emphasise Continuous Learning
Highlight your commitment to continuous learning and development. Share examples of how you've embraced feedback and adapted your approach in previous roles. This aligns well with the company's culture of growth and mentorship.
✨Demonstrate Resilience and Problem-Solving
Prepare to discuss challenges you've faced in your career and how you've overcome them. This will showcase your resilience and determination, qualities that are highly valued in a high-performance culture like the one described in the job posting.