Data Scientist, Machine Learning (Risk)
Location: Palo Alto, CA (hybrid)
NEXT’s mission is to help entrepreneurs thrive. We’re doing that by building the only technology-led, full-stack provider of small business insurance in the industry, taking on the entire value chain and transforming the customer experience.
Simply put, wherever you find small businesses, you’ll find NEXT.
Since 2016, we’ve helped hundreds of thousands of small business customers across the United States get fast, customized and affordable coverage. We’re backed by industry leaders in insurance and tech, and we still have room to grow — that’s where you come in.
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.
What You'll Do:
- 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
What We Need:
- 3-5+ years of hands-on experience in data mining, machine learning and/or statistical analysis
- 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 in Python and the standard numerical packages
- Fluency with data extraction/ manipulation tools (preferably SQL & Pandas)
The US annual base salary range for this full-time position is $113,000 - $210,000. The range displayed on this job posting reflects the minimum and maximum target for new hire salaries for the position in the location(s) listed. Within the range, individual pay is determined by additional factors, including, without limitation, job-related skills, experience, and relevant education or training. NEXT employees also have the opportunity to receive equity and a generous benefits package.
Don’t meet every single requirement? Studies have shown that some underrepresented people are less likely to apply to jobs unless they meet every single qualification. At NEXT, we are dedicated to building a diverse, inclusive and respectful workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
One of our core values is 'Play as a Team'; this means making sure everyone has an equal chance to participate and make a difference. We win by playing together. Next Insurance is an equal opportunity employer and prioritizes building a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants of any type and do not discriminate based on race, color, religion, national origin, gender, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job-related characteristics or other prohibited grounds specified in applicable federal, state, and local laws. Next's policy is to comply with all applicable laws related to nondiscrimination and equal opportunity and will not tolerate discrimination or harassment based on any of these characteristics. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.