Next Insurance is a fast-growing 300 person startup based in Silicon Valley and is led by a team of experienced entrepreneurs with a history of successful outcomes. Our mission is to transform insurance for small businesses by combining world-class technology and phenomenal customer service to offer better insurance at a lower price. Next has raised over $380 million from top tier investors and is the valley’s latest unicorn, valued at over $1 billion.
Next is well-positioned to become the leader in the $140 billion small business insurance market because we offer a 100% online experience that is tailored to unique business needs and we get customers insured in minutes – something no one else does. Despite the size of the market, the experience of buying small business insurance has not caught up with best practices instituted in other industries like banking, lending, and even personal lines insurance. There is still a lot of paper involved, purchasing a policy can take days or even weeks, and the coverage is so complex that it’s hard for entrepreneurs to understand what they are buying. We’re here to change that. Our goal is to make insurance simple, affordable, and transparent for small businesses so they can stop worrying about insurance and focus on running their businesses.
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 will report directly to our Head of Data Science and have day-to-day exposure to multiple members of the company leadership team. You 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.
4+ years of hands-on experience in data mining, machine learning, and/or statistical analysis.
MS/Ph.D. in Computer Science, Statistics, Applied Math, or related areas from a top university.
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 (preferably python) and the standard numerical packages.
Fluency with data extraction/manipulation tools (preferably SQL and pandas).