Palo Alto, California
Data Scientist, Machine Learning
Next Insurance is a well-funded, high-growth post-Series B startup based in Palo Alto, California. We are revolutionizing the insurance industry by providing small businesses with simple, affordable, tailored insurance coverage, leveraging innovative technology and data science for superior customer experience. Compared to other fields undergoing digital and data transformations, this traditional industry has lagged behind and data science has numerous opportunities to add tremendous value.
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 4 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
Desired Skills and Experience:
2+ years of hands-on experience in data mining, machine learning and/or statistical analysis
MS/Phd 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)