Senior Data Engineer - Scientific AI

McKinsey & Company, Inc.

At McKinsey & Company, the Senior Data Engineer - Scientific AI role offers an opportunity to work on intricate challenges alongside ambitious leaders. The role focuses on transforming AI prototypes into practical solutions, enabling seamless implementation in collaboration with client delivery teams. As part of a multidisciplinary team, the engineer will play a key role in advancing McKinsey's scientific AI initiatives across various industries.

In this role you can expect to have the responsibilities:

• Leverage expertise in data/machine learning engineering for complex client problems.
• Support engineering roadmaps and transform AI prototypes into deployment-ready solutions.
• Ensure seamless implementation by working directly with client delivery teams.
• Translate engineering concepts for senior stakeholders and write optimized code.
• Collaborate with multi-disciplinary teams and coach junior colleagues.

This role comes with the following benefits:

• Opportunity to work with cutting-edge AI teams and projects in diverse industries.
• Play a pivotal role in building and shaping McKinsey’s scientific AI offerings.
• Chance to contribute to proprietary assets and gain recognition in your area of expertise.

This role requires you to have:

• Master’s degree with 7-8 years of experience or PhD with 5-7 years of relevant experience
• Data Engineering Experience
• Experience in research
• ETL
• Big Data Tooling (PySpark, Databricks)
• Data Handling (SQL & NoSQL)
• Feature Engineering

You would benefit from having:

• Python Testing Frameworks
• Data Validation and Quality Frameworks
• Graph Data Structures (Neo4j)
• CI/CD Pipelines
• Basic Kubernetes
• Generative AI
• MLflow Deployment