Data Scientist - Financial Services Lab

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. You will apply advanced analytics techniques including predictive modelling, geospatial analysis, generative AI, optimization, and simulation to large-scale datasets at some of the world’s most influential institutions. You will partner with client teams across project settings to drive and produce week-one analyses and enable quick-turn analytics client development work. Many of these analyses will be used to develop solutions and products to craft reusable data-driven insights. You will become an advocate for the use of data and analytics, guiding teams on the proper selection of datasets and analytic strategies to ensure we increase the value of impact we deliver to our clients. This will enable collaboration across other practices, analytics groups, and technical teams to ensure efforts are synergistic and cutting-edge. You will help to maintain and deliver a compelling portrayal of McKinsey’s data ecosystem and capabilities to clients and internal stakeholders. As well as drive awareness of the firm’s policies related to data risk and refine/operationalize KPIs.

Master’s degree in quantitative fields such as Mathematics, Computer Science, Engineering, Physics, or a related discipline 2+ years of professional experience in data science, data engineering, or a closely related field Experience with data engineering practices including ETL pipelines, orchestration tools such as Airflow, and big data platforms like Databricks; hands-on experience with data modelling techniques (e.g., 3NF, data vault, etc.), ability to work with both structured and unstructured data Strong applied data science skills with experience in supervised and unsupervised learning, time series forecasting, clustering, optimization, geospatial modeling, and generative AI; familiarity with libraries such as scikit-learn, XGBoost, LightGBM, PyTorch, Hugging Face Transformers, and pandas Solid engineering capabilities in Python and JavaScript, with hands-on experience building and operationalizing solutions using FastAPI and React Comfortable working with Git, CI/CD tools, and modern development workflows Hands-on experience with large language models (LLMs) and agentic AI, including prompt engineering, retrieval-augmented generation (RAG), tool/function calling, multi-agent workflows, evaluation, and productionizing LLM-powered applications Familiarity with frameworks such as LangChain, LangGraph, LlamaIndex, and major model APIs Familiarity with Azure cloud services; experience with Kubernetes, Docker, and distributed computing frameworks is a plus Highly inquisitive and creative problem-solver with a passion for turning data into actionable insight Entrepreneurial and self-starting mindset, comfortable navigating ambiguity in a fast-paced, dynamic environment Collaborative, professional, and team-oriented, with a strong sense of ownership and service Strong communication skills with the ability to convey complex technical topics to both technical and non-technical audiences