Doximity is transforming the healthcare industry. Our mission is to help doctors save time so they can provide better care for patients.
We value diversity — in backgrounds and in experiences. Healthcare is a universal concern, and we need people from all backgrounds to help build the future of healthcare.
How you’ll make an impact:
- Employ appropriate methods to develop performant machine learning models at scale, owning them from inception to business impact.
- Plan, engineer, and deploy both batch-processed and real-time data science solutions to increase user engagement with Doximity’s products.
- Collaborate cross-functionally with data engineers and software engineers to architect and implement infrastructure in support of Doximity’s data science platform.
- Improve the accuracy, runtime, scalability and reliability of machine intelligence systems
- Think creatively and outside of the box. The ability to formulate, implement, and test your ideas quickly is crucial.
What we’re looking for:
- 3+ years of industry experience; M.S. in Computer Science or other relevant technical field preferred.
- 3+ years experience collaborating with data science and data engineering teams to build and productionize machine learning pipelines.
- Fluent in SQL and Python; experience using Spark (pyspark) and working with both relational and non-relational databases.
- Demonstrated industry success in building and deploying machine learning pipelines, as well as feature engineering from semi-structured data.
- Solid understanding of the foundational concepts of machine learning and artificial intelligence.
- A desire to grow as an engineer through collaboration with a diverse team, code reviews, and learning new languages/technologies.
- 2+ years of experience using version control, especially Git.
- Familiarity with Linux, AWS, Redshift.
- Deep learning experience preferred.
- Work experience with REST APIs, deploying microservices, and Docker is a plus.