Sr. Data Scientist

eHealth Insurance   •  

Santa Clara, CA

Industry: Accounting, Finance & Insurance


Less than 5 years

Posted 37 days ago

Position Summary:

At eHealth, we are passionate about solving our nation's toughest problems to bring more suitable, accessible, and affordable health insurance to Americans. We are seeking an exceptional senior data scientist to join our growing team, which is developing cutting-edge analytic tools to drive better and faster decision making within our company and to better serve our customers. This is a fast-paced, collaborative, and iterative environment requiring quick learning, agility, and flexibility.


  • Participate in all aspects of the project lifecycle from requirements gathering, data acquisition and preparation, hypothesis generation, ideation, coding, testing, and deployment of data science product.
  • Develop state of the art machine learning models. Iterate to push the boundaries on what problems can be solved through data science.
  • Conduct open-ended data exploration to evaluate and improve internal processes.
  • Work with business partners to identify opportunities for innovation.
  • Work closely with engineers to productionize models.

Basic Qualifications:

  • BS or Ph.D. in Computer Science, Statistics, Engineering, or a related quantitative field.
  • 3+ years of industry experience in productionizing machine learning models.
  • 3+ years of experience in writing production codes with at least one software development programming language (Java, Scala), one data programming language (Python, R), and scriptinglanguages (Unix shell) as well as solid experience with git.
  • Mastery of data wrangling libraries (Pandas, Numpy), scientific computing libraries (Scipy, Statsmodels), and machine learning libraries (Scikit-learn,, MLlib, Tensorflow, Keras).
  • Mastery of SQL (Oracle, MSSQL), work experience with distributed querying (Spark SQL) and NoSQL systems (MongoDB).
  • Excellent statistical intuition and knowledge of various analytical approaches such as inference, hypothesis testing, sampling, survival analysis etc.
  • Excellent communication skills in written and verbal forms, and an ability to communicate complex issues to a range of audience (management, peers, clients).

Nice to Have:

  • Experience with AWS ecosystem.
  • Experience with machine learning at scale is a big plus.
  • Experience with machine learning stack optimization.
  • Experience with experimental design and multivariate experiments.
  • Experience with text data and NLP is a big plus.
  • Experience with Deep Learning.