The Lead Data Scientist architects, builds, and runs production-grade Machine Learning and Generative AI systems—owning the full lifecycle from model development to scalable cloud deployment and ongoing performance monitoring
Job Summary
The Lead Data Scientist architects, builds, and runs production-grade Machine Learning and Generative AI systems—owning the full lifecycle from model development to scalable cloud deployment and ongoing performance monitoring.
The role plays a critical part in establishing a single source of truth for performance management across markets and channels while elevating analytics maturity from descriptive reporting to predictive and insight-led decision making.
We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve.
Matching Summary
The Lead Data Scientist architects, builds, and runs production-grade Machine Learning and Generative AI systems—owning the full lifecycle from model development to scalable cloud deployment and ongoing performance monitoring.
Skills & Requirements
Must-have
ML & Deep Learning Model Development
GenAI Engineering (LLMs, RAG)
ML & LLM Operations Productionization
Pipeline Orchestration & Automation
Python (production-quality coding)
SQL for data access and validation
Deep learning framework (PyTorch/TensorFlow)
Nice-to-have
Builder and translator mindset
Continuous learning mindset
Applied problem-solving focus
Influence senior stakeholders
Health technology company
Key Requirements
7–12+ years in hands-on Data Science / ML Engineering
Bachelor’s degree in quantitative field
Master’s degree preferred
Proven track record of owning end-to-end analytics domains
Demonstrated ability to take solutions from experimentation → production