At a Glance
- Tasks: Develop AI models and support client discussions in a dynamic, multi-disciplinary team.
- Company: Join McKinsey's global scientific AI team, known for innovation and collaboration.
- Benefits: Competitive salary, comprehensive benefits, and a focus on holistic well-being.
- Other info: Experience a culture of continuous learning and diverse perspectives.
- Why this job: Make a real impact with cutting-edge technology while growing your skills rapidly.
- Qualifications: Master’s or PhD with 2+ years in statistics, mathematics, or computer science.
The predicted salary is between 60000 - 80000 £ per year.
Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You’ve come to the right place.
YOUR IMPACT
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 or Wroclaw 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 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'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:
- 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 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 and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain). R and C++ optional.
- 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 in London employer: Mckinsey & Company, Inc.
At McKinsey & Company, we pride ourselves on being an exceptional employer, particularly for those in the Data Scientist - Scientific AI role. Our London and Wroclaw offices foster a collaborative and innovative work culture where your contributions are valued from day one, and you will have access to world-class mentorship and continuous learning opportunities. With a commitment to diversity and a comprehensive benefits package, we empower our employees to thrive both personally and professionally while making a meaningful impact in the field of AI and beyond.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Scientific AI in London
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We think you need these skills to ace Data Scientist - Scientific AI in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Mckinsey & Company, Inc., your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Mckinsey & Company, Inc.. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Mckinsey & Company, Inc.
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Mckinsey & Company, Inc.!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
