Wave is a McKinsey SaaS product that equips clients to successfully manage improvement programs and transformations. Focused on business impact, Wave allows clients to track the impact of individual initiatives and understand how they affect longer term goals. It is a mix of an intuitive interface and McKinsey business expertise that gives clients a simple and insightful picture of what can otherwise be a complex process by allowing them to track the progress and performance of initiatives against business goals, budget and time frames.

Our Transformatics team builds data and AI products to provide analytics insights to clients and McKinsey teams involved in transformation programs across the globe. The current team is composed of data engineers, data scientists and product managers who are spread across several geographies. The team covers a variety of industries, functions, analytics methodologies and platforms – e.g. Cloud data engineering, advanced statistics, machine learning, predictive analytics, MLOps and generative AI.

What You'll Do

You will collaborate closely with a team comprising data scientists, data engineers, product developers, and analytics-focused consultants.

You will also be expected to guide more junior colleagues on different analytics topics: descriptive analytics, predictive models (e.g. boosted trees), LLMs (especially for segmentation use-cases) and the ways of working & tooling to do develop & maintain efficiently (MLOps). All this to bring advanced analytics capabilities into one of the firm's flagship products, named "Wave." Your work will be the backbone for how McKinsey runs future Transformations, leveraging data science assets, to lead to our client's success.

In this role you will be responsible for the following:

Technical leadership:Collaborating with product management and your team to design and build true analytics products which are performant, robust, and maintainable. You will help set standards for our data-science approaches, way-of-working, expected quality to build a strong DS product and team
Coaching junior team members:As a senior Data scientist, you will spend a significant portion of your time coaching more junior team members and helping them improve their mastery of the data science domain.
Machine learning model development:Lead the design and refinement of statistical models, optimization techniques, advanced machine learning, and predictive models
LLM optimization and evaluation:Fine-tune and evaluating the performance and efficiency of Large Language Models, leveraging the latest advancements in neural network architectures and machine learning techniques
Advanced insight generation:Provide deep analytical insights to guide client project directions, transforming complex data analyses into actionable insights.
Knowledge and research:Contribute to influential articles, white papers, and research, positioning the firm as a thought leader in analytics and transformation, with a focus on LLMs and predictive modeling
Expert guidance for client teams:Work closely with global client service teams to deliver high-quality advanced analytics solutions, offering expert guidance to ensure analytical excellence in all engagements

Qualifications

Advanced degree in a quantitative field like computer science, machine learning, applied statistics or mathematics; or equivalent experience
3+ years of experience in data science, statistical modelling (e.g. advanced regressions, clustering, classification models) and machine learning techniques (e.g. random forest, support vector machines, gradient boosting, XGBoost)
Experience coaching and mentoring more junior colleagues in the field of data science
Familiarity with neural network architectures (Transformers), RAG models, deep learning libraries (TensorFlow/PyTorch) and machine learning libraries (scikit-learn)
Programming experience in the following languages: Python and SQL
Experience in leading complex engagements to deploy advanced analytics and data science methods at scale in real world organizations
Exposure to tools like Excel, VBA, Snowflake and Tableau is a plus
Strong data translation and presentation skills, able to clearly and effectively communicate complex analytical and technical content are very strong assets for a candidate

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FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity/Affirmative Action 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.

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.

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