Data Scientist - Financial Services Lab

Experteer Overview In this role you will apply advanced analytics to large datasets to drive client impact and shape scalable solutions.You will work with cross-functional client teams to deliver week-one analyses and rapid analytics development, turning data into actionable insights.You join a collaborative, growth-focused culture that emphasizes apprenticeship, mentorship, and ethical, data-driven decision making.This opportunity offers exposure to a global, diverse network and a chance to build lasting capabilities in a high-performance environment.Compensaciones / Beneficios* Apply advanced analytics techniques to large-scale datasets and generate actionable insights* Partner with client teams to deliver initial analyses and rapid analytics development* Develop data-driven solutions and reusable insights for client outcomes* Advocate for effective data usage and guide dataset and analytic strategy choices* Collaborate across practices and technical teams to ensure integrated, cutting-edge delivery* Maintain and communicate McKinsey’s data ecosystem and capabilities to clients and internal stakeholders* Promote awareness of data risk policies and refine KPIs for measured impactResponsabilidades* Master’s degree in a quantitative field* 2+ years of professional experience in data science or data engineering* Experience with ETL, Airflow, and big data platforms (Databricks)* Proficiency in data modeling (3NF, data vault) and working with structured and unstructured data* Strong applied data science skills (supervised/unsupervised learning, time series, geospatial modeling, generative AI)* Familiarity with libraries (scikit-learn, XGBoost, LightGBM, PyTorch, Hugging Face Transformers, pandas)* Solid Python and JavaScript engineering capabilities; experience with FastAPI and React* Experience with Git, CI/CD, and modern development workflows* Familiarity with Azure; Kubernetes, Docker; distributed computing a plus* Inquisitive, creative problem-solver with entrepreneurial, self-starting mindset* Collaborative, ownership-driven, client-service attitude* Strong communication skills to explain complex topics to technical and non-technical audiencesRequisitos principales* competitive salary* comprehensive benefits package* world-class learning and apprenticeship culture* global community across 65+ countries

• Master’s degree in a quantitative field
• 2+ years of professional experience in data science or data engineering
• Experience with ETL, Airflow, and big data platforms (Databricks)
• Proficiency in data modeling (3NF, data vault) and working with structured and unstructured data
• Strong applied data science skills (supervised/unsupervised learning, time series, geospatial modeling, generative AI)
• Familiarity with libraries (scikit-learn, XGBoost, LightGBM, PyTorch, Hugging Face Transformers, pandas)
• Solid Python and JavaScript engineering capabilities; experience with FastAPI and React
• Experience with Git, CI/CD, and modern development workflows
• Familiarity with Azure; Kubernetes, Docker; distributed computing a plus
• Inquisitive, creative problem-solver with entrepreneurial, self-starting mindset
• Collaborative, ownership-driven, client-service attitude
• Strong communication skills to explain complex topics to technical and non-technical audiences

• competitive salary
• comprehensive benefits package
• world-class learning and apprenticeship culture
• global community across 65+ countries