Next Insurance Careers – Data Scientist – Machine Learning Date Posted 23rd Sep 2020


Next Insurance Careers – Data Scientist, Machine Learning. Those Candidate Are Interested to the Following Recruitment and Completed the All Eligibility Criteria Can Read the Full Details Before Apply Online.

Company Name: Next Insurance

Job Position: Data Scientist, Machine Learning

Job Location: Palo Alto – California

Job Description:

  • We are looking for a driven Data Scientist to help us bring machine learning to the insurance industry. As a data scientist at Next Insurance, you will work on a wide range of projects, including building predictive risk models, fine-tuning user experience, and optimizing internal operations. You will enable us to make the best use of our proprietary data, supplemented with novel data sources which you get to assemble creatively.
  • You’ll also have day-to-day exposure to multiple members of the company leadership team and will be joining a small, nimble team of 5+ scientists, with lots of room for growth and impact.


  • Research and develop predictive models (we typically start with a POC and then work with Product and Engineering counterparts to transition to production)
  • Iterate and pivot quickly to deliver MVP solutions. Design quick experiments to maximize learning
  • Understand the data and dig deep to extract actionable insights
  • Think creatively and outside the box to answer desired experimental questions
  • Work cross-functionally with engineering, product, marketing, business intelligence, insurance operations, customer support, senior management, and external partners

Eligibility Criteria:

Desired Skills and Experience:

  • 2-4 years of hands-on experience in data mining, machine learning and/or statistical analysis
  • BS/MS in Computer Science, Statistics, Applied Math, or related areas
  • Experience in writing both agile exploratory analyses as well as production-level code in a fast-paced environment
  • Ability to communicate the results of analyses clearly and effectively
  • Fluency with an analytical programming language (APL) (preferably Python) and the standard numerical packages
  • Fluency with data extraction/manipulation tools (preferably SQL & Pandas)
  • Not Mentioned
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