Data Scientist - Scientific AI, Life Sciences

McKinsey & Company • Philadelphia, PA • 2w ago

Analytics Data Scientist - Scientific AI, Life Sciences Job ID: 94898

Do you want to work on complex and pressing challenges-the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you've come to the right place. Your Impact

Your role will be split between developing new internal knowledge, building AI and machine learning models & pipelines, supporting client discussions, proto@type 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.

Your Growth

You will be working in one of our offices in North America 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

Please review the additional requirements regarding essential job functions of McKinsey colleagues.

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FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law. Certain US jurisdictions require McKinsey & Company to include a reasonable estimate of the salary for this role. For new joiners for this role in the United States, including all office locations where the job may be performed, a reasonable estimated range is $112,900 - $116,500 USD -to help you understand what you can expect. This reflects our best estimate of the lowest to highest [salary/hourly wages] for this role at the time of this posting, ensuring you have a clear picture right from the start, though it's important to remember that actual salaries may vary. Factors like your office location, your unique blend of experience and skills, start date and our current organizational needs all play a part in determining the final figure. Certain roles are also eligible for bonuses, subject to McKinsey's discretion and based on factors such as individual and/or organizational performance. Additionally, we provide a comprehensive benefits package that reflects our commitment to the wellness of our colleagues and their families. This includes medical, mental health, dental and vision coverage, telemedicine services, life, accident and disability insurance, parental leave and family planning benefits, caregiving resources, a generous retirement contributions program, financial guidance, and paid time off. FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites. Job Skill Group - N/A Job Skill Code - TCYB - Data Scientist I Function - Technology Industry - High Tech;Life Sciences Post to LinkedIn - #LI-DNI Posted to LinkedIn Date - LinkedIn Posting City - LinkedIn Posting State/Province - LinkedIn Posting Country - LinkedIn Job Title - Data Scientist - Scientific AI, Life Sciences LinkedIn Function - LinkedIn Industry - LinkedIn Seniority Level -

Equal Opportunity Employment Disclaimer

McKinsey & Company is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, national origin, disability, veteran status, and other protected characteristics.

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