Commercial Data Scientist

Role overview

Use statistical analysis, machine learning, and AI to turn large clinical and professional behavior datasets into insights for client organizations. You’ll work across analytics, engineering, product, and commercial teams, while building reusable data products and communicating findings to technical and business audiences.

Responsibilities

- Analyze large structured and unstructured datasets to identify and classify patterns in healthcare professionals’ platform activity. - Develop client-facing analyses that support data-informed decisions. - Design, train, and evaluate production-scale machine learning models. - Build data products and automate analysis code so it can be reused across projects. - Present technical findings as clear, useful narratives for clients and internal stakeholders. - Partner with colleagues across product, data, strategy, and sales in a fast-paced delivery environment.

Requirements

- At least four years of professional experience in data science or a related role working with complex, high-volume datasets. - Advanced knowledge of statistical methods, including exploratory analysis, experimental design, and probability. - Strong understanding of modern machine learning and experience building production models with PyTorch or TensorFlow. - Advanced SQL skills, including writing and optimizing queries across multiple tables. - Advanced Python skills, including object-oriented programming, production-quality code, and data science libraries. - Experience with distributed data processing, plus the ability to explain analytical results clearly.

Nice to have

- Experience in data science consulting and fast-paced client delivery. - Ongoing curiosity about data and machine learning research, with a habit of learning beyond immediate project needs.

Benefits and work setup

The role may be based in the northeastern United States, at a San Francisco office, or remotely elsewhere in the U.S. Visa sponsorship is unavailable. Full-time benefits include medical, dental, and vision coverage; a matched retirement plan; flexible paid time off and holidays; parental leave; professional development; wellness resources; and remote-work support or a home-office stipend where applicable.