Overview
The role of Commercial Data Scientist at Doximity involves working within cross-functional delivery teams to discover data insights that can enhance healthcare. Doximity is a leading clinical AI company with a vast network of U.S. clinicians.
Key Responsibilities
- Deliver novel and impactful insights for client organizations using machine learning and AI technologies.
- Collaborate with Product, Platform Data, Insights & Strategy, and Sales teams to create client-facing analyses.
- Create data products from scratch and automate code for reuse in future projects.
- Leverage extensive datasets to identify and classify behavioral patterns of medical professionals on the platform.
- Exceed client expectations in a fast-paced environment.
Requirements
- At least 4 years of professional experience as a Data Scientist or in similar roles with complex datasets.
- Prior data science consulting experience preferred.
- Advanced knowledge of statistical concepts, exploratory data analysis, and machine learning techniques.
- Proficient in designing, training, and evaluating large-scale production models with frameworks like PyTorch or TensorFlow.
- Advanced SQL and Python skills, including knowledge of object-oriented programming and modern data science libraries.
- Hands-on experience with distributed data processing tools.
- Excellent data visualization and storytelling abilities.
- A curious and fast learner with a passion for data and continuous learning.
Benefits
- Medical, dental, and vision insurance.
- 401(k) with company match.
- Flexible paid time off and company holidays.
- Paid parental leave.
- Professional development and learning opportunities.
- Wellness and mental health resources.
- Remote work support and home office stipend.
Location
This role can be filled in remote locations across the U.S. or at Doximity's headquarters in San Francisco or offices in the Northeast (New York, NJ, Philadelphia, Boston).
How to Apply
Interested candidates should apply through the Doximity career page.
Deadline
No specific deadline stated.