Senior Data Engineer - Scientific AI, Life Sciences
McKinsey & Company
Job Description
About the Role
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.
Key Responsibilities
- Bringing distinctive data/machine learning engineering & product development competency to complex client problems through part-time staffing on clients
- Supporting the manager of data engineering/machine learning engineering on the development of data/machine learning engineering roadmap of assets across cell-level initiatives
- Productionize AI prototypes/create deployment ready solutions
- Translating engineering concepts and design/architecture trade-offs and decisions for senior stakeholders
- Writing optimized code to advance our AI Toolbox and codify methodologies for future deployment
- Working in a multi-disciplinary team
- Coaching/mentoring junior colleagues
Requirements
- Master's degree with 5+ years or PhD degree with 2+ years of relevant experience in computer science, computer engineering or equivalent experience with experience in research
- ETL, big data experience and tooling (i.e., PySpark, Databricks), Python testing frameworks, data validation and data quality frameworks, data handling (SQL & NoSQL), feature engineering, chunking, document ingestion, graph data structures (i.e., Neo4j), CI/CD pipelines, basic K8s (manifests, debugging, docker, Argo Workflows), MLflow deployment and usage, GenAI frameworks (LangChain), GPU model development / deployment
- Proven experience applying machine learning techniques to solve business problems
- Experience in client delivery with direct client contact
- Proven experience in translating technical methods to non-technical stakeholders
- Strong programming experience in python (Python, Java, C++, SQL) and experience with cloud development platforms such as AWS, Azure, Google (and appropriate Bash/Shell scripting)
- Experience with version control (GitHub)
Nice to Have
- Ability to write production code and object-oriented programming is a plus
Qualifications
- Master's degree with 5+ years or PhD degree with 2+ years of relevant experience in computer science, computer engineering or equivalent experience
Benefits & Perks
- Competitive salary (based on your location, experience, and skills)
- Comprehensive benefits package, including medical, dental, mental health, and vision coverage for you, your spouse/partner, and children
Working at McKinsey & Company
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. We value your ideas and contributions from day one, encouraging diverse perspectives to drive the best outcomes. With colleagues across 65+ countries and over 100 nationalities, our firm's diversity fuels creativity and helps us come up with the best solutions for our clients. You'll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
Job Details
About McKinsey & Company
Website
mckinsey.com
Company Size
10000+ employees
Location
Seattle, WA
Industry
Management Consulting Services
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