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Senior Data Scientist - McKinsey Transformation Job ID: 93730Do 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 ImpactYou will collaborate closely with a team comprising data scientists, data engineers, product developers, and analytics-focused consultants.
You will work on topics such as descriptive analytics, predictive models (e.g., boosted trees), and large language models (LLMs), particularly for segmentation use cases. Additionally, you will design and deliver products that adhere to MLOps best practices, ensuring they are both maintainable and deployable. By doing so, you will help bring advanced analytics capabilities into one of McKinsey's flagship products, named "Wave". Your work will be the backbone for how McKinsey runs future Transformations, leveraging data science assets, to improve the odds of success for our clients.
In this role, you will be responsible for the following, as the primary focus:
- Advanced insight generation: transforming complex business questions into statically relevant analyses and these analyses into easy to digest insights. Delivering this through well documented and tested pipelines, that allow easy collaboration with other team members.
- Upholding technical excellence: Together with the tech lead(s) define how to build, maintain and scale our pipelines. Often piloting new technical approaches & automation. Using your business understanding to critically review model results, trends, analyses and classifications.
- Coach & help other colleagues: Coach & help you peers when needed, we deliver as a team.
- 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
Your role might also include, as the secondary focus:
- Design & build creative approaches to further optimize accuracy & reduce cost:In addition to optimizing the LLM through prompts and settings, you will design and test alternative approaches, such as pre-filters and non-LLM-based text models, within parallel multi-agent setups.
- Build for scale: Together with the tech lead(s), you will define how to maintain and scale our LLM classifier pipeline. The classifier pipeline will, in the long term, run as a on-demand batch process, and will, once stable, be refactored with scalability in mind.
- Deploying pipelines at scale: Although not core to your role, you will be exposed to cloud deployments & orchestration of our pipelines and can shape these if you have an interest in this field.
- Expert guidance for client teams: You will work closely with global client service teams to deliver high-quality advanced analytics solutions, offering expert guidance to ensure analytical excellence and understanding at client teams.
- Knowledge and research: You will 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
You will work in our McKinsey Transformation Client Capabilities Network in EMEA and will be part of our Wave Transformatics team.
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.
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. 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 qualifications and skills- Familiarity with neural network architectures (Transformers), RAG models, deep learning libraries (TensorFlow/PyTorch) and machine learning libraries (scikit-learn) is a plus
- Exposure to extra tooling such as Snowflake, Excel and Tableau is a plus
- Experience in leading complex engagements to deploy advanced analytics and data science methods at scale in real world organizations
- Programming experience in the following languages: Python and SQL
- 3+ years of relevant experience with classical descriptive statistics, standard statistical modelling (e.g. advanced regressions, clustering, classification models) and machine learning techniques (e.g. random forest, support vector machines, gradient boosting, XGBoost)
- Strong data translation and presentation skills with the ability to clearly and effectively communicate complex analytical and technical content
- MSc or PhD level in the field of computer science, machine learning, applied statistics, mathematics or equivalent by experience
Please review the additional requirements regarding essential job functions of McKinsey colleagues.
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.
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.
