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This job is open to applicants residing anywhere within the United States and Canada.
Why work at Doximity?
Doximity is rewiring healthcare and is the 6th fastest growing technology company in North America. Here's how clinicians use our products. For us, transparency is key, so ensuring your goals and values align with ours is also an important step. Take a look at how we Work at Doximity.
Skills & Requirements:
- M.S./Ph.D. or equivalent experience (4+ years) 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, deep learning) and parameters that affect their performance.
- Expert knowledge of probability and statistics (e.g., experimental design, optimization, predictive modeling).
- Experience with recommendation algorithms and strong knowledge of machine learning concepts.
- Solid engineering skills to build scalable solutions and help automate data processing challenges.
- Excellent problem-solving skills and ability to connect data science work to product impacts.
- Expertise in SQL and Python.
- Familiarity with AWS, Redshift, Spark.
What you can expect:
- Employ scalable statistical methods, machine learning and NLP methods to build and improve models using large sets of real user data.
- Leverage knowledge of recommendation algorithms to improve user engagement by personalizing delivered content.
- Experiment with features and parameters to optimize user retention and engagement.
- Collaborate with a team of product managers, analysts, data engineers, data scientists, and other developers.
- Think creatively and outside of the box. The ability to implement and test your ideas quickly is crucial.
- We historically favor Python and MySQL, but leverage other tools when appropriate for the job at hand.
- Machine learning (linear/logistic regression, ensemble-models, boosted-models, clustering, NLP, text categorization, user modeling, collaborative filtering, etc) via industry-standard packages (sklearn, nltk, MLlib, GraphX, NetworkX, gensim).
- A dedicated cluster is maintained to run Apache Spark for computationally intensive tasks.
- Storage solutions: Percona, Redshift, S3, HDFS, Hive, neo4j.
- Computational resources: EC2, Spark.
- Workflow management: Airflow.
Fun facts about the Data Science team:
- We have access to one of the richest health care datasets in the world, with deep information on hundreds of thousands of healthcare professionals and their connections.
- We build code that addresses user needs, solves business problems, and streamlines internal processes.
- The members of our team bring a diverse set of technical and cultural backgrounds.
- Business decisions at Doximity are driven by our data, analyses, and insights.
- Hundreds of thousands of healthcare professionals will utilize the products you build.
- A couple times a year we run a co-op where you can pick a few people you'd like to work with and drive a specific company goal.
- We like to have fun - company outings, team lunches, and happy hours!
- Full medical, vision, dental for you and your family.
- Stock, pre-IPO stock incentives.
- 3+ weeks of vacation (another week off during the December Holidays)
- 401K and flexible spending accounts.
- Life insurance and disability insurance coverage.
- Brand new computer.
- All-company trips in fun places like Beverly Hills, Lake Tahoe, and Puerto Vallarta, Mexico
Doximity is the leading online medical network with over 70% of U.S. doctors as members. We have strong revenues, profits, real market traction, and we’re putting a dent in the inefficiencies of our $2.5 trillion U.S. healthcare system. After the iPhone, Doximity is the fastest adopted product by doctors of all time. Launched by Jeff Tangney in 2011; Jeff previously founded healthcare pioneer Epocrates (NASDAQ: EPOC). Our beautiful offices are located in SoMa San Francisco.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.