Commercial Data Scientist

Doximity; United States; Remote; USD 120,000 - 190,000; Full time

Job summary

Doximity is a leading clinical AI company with a network of U.S. clinicians. The Commercial Data Scientist will collaborate with product, data, insights, and sales teams to uncover insights from large datasets and build data products for clients.

The role emphasizes delivering impactful analyses, automating workflows, and applying machine learning to healthcare datasets in a fast-paced environment. Remote-friendly within the U.S.

Qualifications

• At least 4 years of professional experience as a Data Scientist or related role.
• Experience with complex, high-volume, structured and unstructured datasets.

Responsibilities

• Deliver novel and impactful insights for client organizations using machine learning and AI technologies.
• Work closely with Product, Platform Data, Insights Strategy, and Sales teams to create client-facing analyses.
• Showcase engineering skills by creating data products from scratch and automating code for reuse across projects.

Job description

Commercial Data Scientist

Doximity is the leading clinical AI company with the largest network of U.S. clinicians. Doximity’s AI-powered workflow platform is trusted by over 85% of U.S. physicians and 300+ health systems. Doximity's mission is to help clinicians be more productive so they can provide better care for their patients.

At Doximity, we value curiosity, ownership, inclusion, and a commitment to making a meaningful impact. If you're excited about solving complex problems that improve healthcare, we'd love to hear from you.

This role can be filled in the Northeast (New York, NJ, Philadelphia, Boston), our San Francisco headquarters, OR other remote locations in the U.S.

As a Commercial Data Scientist, you’ll work within cross-functional delivery teams alongside other analysts, engineers, and commercial stakeholders in discovering data insights to help improve healthcare.

How you’ll make an impact:

• Deliver novel and impactful insights for client organizations using machine learning and AI technologies.
• Work closely with our Product, Platform Data, Insights Strategy, and Sales teams to create client-facing analyses.
• Showcase your engineering skills by creating data products from scratch and automating code so they can be re-used by other teammates and future projects.
• Leverage Doximity's extensive datasets to identify and classify behavioral patterns of medical professionals on our platform.
• Embrace the challenge of a fast-paced environment to exceed client expectations

The Core Values of the Client Intelligence team

As an organization we value diversity - in backgrounds and in experiences. Healthcare is a universal concern, and we need people from all backgrounds to help build a better future for all. Below are additional core values specific to the Insights Team.

• Collaboration—The best candidates and teammates are not only strong in their own aptitudes but care deeply about supporting each other's growth.
• Passion for Data—You’re going to help our clients and team members with data-driven decision making. We need someone that can manipulate millions of rows of data and also ask the right questions to find the important insights.
• Reliability – Our team is efficient, flexible, and agile only because we trust the reliability of each member. We need self-starters and goal-oriented individuals for our continued success.
• Curiosity – Continuous learning is a cornerstone at Doximity, and curious individuals thrive in our environment. We’re looking for someone who is curious enough about data to go above-and-beyond the task for the true insight.
• Respect – A key dynamic that allows our team to flourish is respect: for ourselves and our quality of work, for our teammates, and for our internal clients who are under the pressure of deadlines and finance goals.

About you:

At least 4 years of professional experience as a Data Scientist or other related roles working with complex, high-volume, structured and unstructured datasets.
Prior exper