Senior Data Scientist

Nirvana is on a mission to harness the power of data to revolutionize commercial insurance and enable a safer world. We are bringing much-needed innovation into the legacy, trillion-dollar commercial insurance industry. We have developed cutting-edge predictive models that use real-time IoT data from billions of connected devices, allowing us to better understand and price risk. Our AI-driven platform fundamentally changes the way an insurance company operates with personalized risk scoring, faster underwriting, modernized claims, and proactive, data-driven insights to help customers prevent accidents.

We've already proven the scale—reaching well over $100 million in premiums and more than doubling year over year. Our data moat is growing exponentially with more than 20 billion miles of telematics data, leading to more predictive models and new insights into how we can better understand and reduce risk. Altogether, our loss ratio, efficiency, and customer experience are redefining what can be done in the industry.

With $170+ million raised, including an industry-leading Series C round in January 2025, we're only accelerating our growth, with strong support from top-tier VCs including Lightspeed, General Catalyst, and Valor. Nirvana's leadership team has previously helped scale multi-billion-dollar companies from scratch, including Samsara, Rubrik, and Flexport, and includes industry veterans from Hiscox, The Hartford, and RLI.

At Nirvana, we work with heterogeneous datasets and mine predictive signals to accurately identify risks for businesses. Some of the data we work with includes:

• 100s of millions of GPS and sensor data points per vehicle, ingested and stored in our proprietary data platform.

• Safety events like harsh braking, distracted driving, etc computed from sensors in commercial vehicles.

• High-dimensional datasets containing, among others, decades of vehicle inspection, crash, and violation data for all commercial vehicles in the US.

As a Senior Data Scientist, not only will you execute the data science team's projects and move the agenda forward, you will also work closely with our data engineering and insurance teams and use these large datasets to help build data-driven insurance and safety products in a fast-paced startup environment. You must enjoy working with large data and finding interesting patterns in the data through analytics experiments in a methodical and data-driven scientific way.

The insurance / risk business has many unsolved problems where sophisticated use of information plays a critical role. Join us in making an impact on the industry

• Serves as the lead modeler on larger projects or works on concurrent projects E2E

• Work closely with the insurance team to build and validate complex risk models

• Extract actionable insights and recommendations from time series data to help our customers improve their safety

• Understand data characteristics, prepare and clean large high-dimensional data sets, and define and automate robust data quality measures

• Identifies creative solutions to complex business problems of broad scope and business impact

• Interprets data analysis and model results for business and technical teams

• Standardize analysis methodology and building automation frameworks

• Accurately performs peer reviews across a broad spectrum of work

• Work in cross functional teams

• Supports recruitment needs

• Graduate degree in a quantitative or technical discipline and/or 6+ years of applying advanced quantitative techniques to problems in industry

• Strong demonstrable knowledge of topics such as statistical inference, predictive analytics, probability theory, machine learning, etc

• Proven track record with design, development, implementation, and monitoring of statistical and machine learning models independently

• Strong technical (written and verbal) communication, prioritization, and time management skills 

• Strong programming skills with experience using modern packages in Python

• Demonstrated experience building, validating, and applying statistical machine learning methods to real world problems

• Demonstrated experience in co-creating data science platforms for efficient scaling of research and outputs; from early stages to mature processes

• Competitive compensation & meaningful equity

• Health insurance for you and your family

• Monthly wellness stipend

• Hybrid culture and reimbursement for home office equipment

• A flexible vacation policy and a team that understands building a company is a marathon, not a sprint

• A culture that gives you the autonomy you need to do great work, and the transparency you need to make good decisions

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