Doximity: Senior Data Scientist, Newsfeed
Headquarters: San Francisco, CA
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. Our data science team is deliberate and self-reflective about the kind of data team and culture that we are building, seeking data scientists and engineers that are not only strong in their own aptitudes but care deeply about supporting each other’s growth. We have one of the richest healthcare datasets in the world, and our team brings a diverse set of technical and cultural backgrounds.
Doximity’s social network has over 70% of US doctors as members. We recently launched a newsfeed which helps physicians navigate the latest practice-changing medical literature, parsing through millions of scientific studies while personalizing content to their patient base and every stage of their medical career. We’re looking for a deep learning expert to help our data science and engineering teams build models in support of the newsfeed, combining metadata from our clinician social graph with text-based features.
How you’ll make an impact:
- Apply NLP methods and build deep neural networks to personalize medical content to our clinician members.
- Optimize the layout of different content types (e.g., journal articles, news articles, video, social updates) within the newsfeed.
- Collaborate with data engineers to devise plans to refresh the newsfeed and surface optimized content to users near real-time.
- Provide technical leadership to other data scientists and data engineers working on the newsfeed product.
What we’re looking for:
- 4+ years of industry experience and M.S./Ph.D. in Computer Science, Engineering, Statistics, or other relevant technical field.
- 4+ years experience with various machine learning methods (classification, clustering, natural language processing, ensemble methods) and parameters that affect their performance.
- Experience building deep neural networks in support of recommendation systems.
- Solid engineering skills to build scalable solutions and help automate data processing challenges.
- Desire to provide technical leadership and mentorship to other data team members.
- Expert knowledge of probability and statistics (e.g., experimental design, optimization, predictive modeling).
- Excellent problem-solving skills and ability to connect data science work to product impacts.
- Fluent in SQL and Python; experience using Apache Spark (pyspark).
- Experience working with relational and non-relational databases.
Nice to have:
- Experience applying reinforcement learning to industry problems.
We’re thrilled to be named the Fastest Growing Company in the Bay Area, and one of Fast Company’s Most Innovative Companies. Joining Doximity means being part of an incredibly talented and humble team. We work on amazing products that over 70% of US doctors (and over one million healthcare professionals) use to make their busy lives a little easier. We’re driven by the goal of improving inefficiencies in our $2.5 trillion U.S. healthcare system and love creating technology that has a real, meaningful impact on people’s lives. To learn more about our team, culture, and users, check out our careers page, company blog, and engineering blog. We’re growing fast, and there’s plenty of opportunity for you to make an impact—join us!
Doximity is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.
To apply: https://grnh.se/oj8un01