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Senior Data Scientistverified
Senior Data Scientist
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.\n##Skills & Requirements\n- 4+ years of industry experience and M.S./Ph.D. in Computer Science, Engineering, Statistics, or other relevant technical field.\n- 4+ years experience with various machine learning methods (classification, clustering, natural language processing, ensemble methods, deep learning) and parameters that affect their performance.\n- Expert knowledge of probability and statistics (e.g., experimental design, optimization, predictive modeling).\n- Experience with recommendation algorithms and strong knowledge of machine learning concepts.\nSolid engineering skills to build scalable solutions and help automate data processing challenges.\n- Excellent problem-solving skills and ability to connect data science work to product impacts.\n- Fluent in SQL and Python; experience using Apache Spark (pyspark) and working with both relational and non-relational databases.\n- Familiarity with AWS, Redshift.\n\n##What you can expect\n- Employ scalable statistical methods and NLP methods to develop machine learning models at scale, owning them from inception to business impact.\n- Leverage knowledge of recommendation algorithms to increase user engagement through personalization of delivered content.\n- Plan, engineer and measure outcomes of online experiments to help guide product development.\n- Collaborate with a team of product managers, analysts, data engineers, data scientists, and other developers.\n- Think creatively and outside of the box. The ability to implement and test your ideas quickly is crucial.\n\n##Technical Stack\n- We historically favor Python and MySQL, but leverage other tools when appropriate for the job at hand.\n- Machine learning (linear/logistic regression, ensemble-models, boosted-models, clustering, NLP, text categorization, user modeling, collaborative filtering, etc) via industry-standard packages (sklearn, nltk, -Spark ML/MLlib, GraphX/GraphFrames, NetworkX, gensim).\n- A dedicated cluster is maintained to run Apache Spark for computationally intensive tasks.\n- Storage solutions: Percona, Redshift, S3, HDFS, Hive, neo4j.\n- Computational resources: EC2, Spark.\n- Workflow management: Airflow.\n\n##Fun facts about the Data Science team\n- We have access to one of the richest healthcare datasets in the world, with deep information on hundreds of thousands of healthcare professionals and their connections.\n- We build code that addresses user needs, solves business problems, and streamlines internal processes.\n- The members of our team bring a diverse set of technical and cultural backgrounds.\n- Business decisions at Doximity are driven by our data, analyses, and insights.\n- Hundreds of thousands of healthcare professionals will utilize the products you build.\n- 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.\n- We like to have fun - company outings, team lunches, and happy hours!
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