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# Data Scientist

- **Company:** Doximity, Inc.
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $110,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Distributed Computing Environment, Python (Programming Language), NumPy, Object-Oriented Software Development, Standard Sql, Data Ingestion, Pandas
- **Published:** October 27, 2026
- **Apply:** https://www.adzuna.com/details/5941200456

## About the Role

* At least 2 years of professional experience as a data analyst or a data scientist.
 * Knowledge of statistical concepts, especially exploratory data analysis techniques, and probability theory.
 * Excellent SQL skills to create and evaluate complex statements involving numerous tables and data relationships.
 * Excellent visualization and storytelling skills to explain your results and solutions to the stakeholders, clearly and compellingly.
 * Proficient in using Python data analysis libraries such as Pandas and Numpy. Also has a basic understanding of the object-oriented programming concepts as it relates to Python.
 * Prior exposure to distributed data processing concepts and execution (e.g., working with column stores, leveraging spark, etc.)
 * Fast learner; curiosity about and passion for data.

## Description

As a Data Scientist, you'll work within cross-functional delivery teams alongside other data scientists, engineers, and product managers in discovering data insights to help improve healthcare.

Here's How You Will Make an Impact

 * Leverage Doximity's extensive datasets to identify and classify behavioral patterns of medical professionals on our platform.
 * Play a key role in creating both product and client-facing analytics.
 * Inform data team strategy by working with the product leaders and managers. Actively participate in execution and some planning of organizational data team strategy.
 * Collaborate with a team of product managers, analysts, and other developers to define and lead data projects from data ingestion to analysis to recommendations.