Data Scientist

About the role

North saves customers money by buying and managing cloud commitments on their behalf. Every recommendation depends on predicting how a customer's usage will change, and every mistake costs real money, either in missed savings or in commitments that go unused.

You'll join the Commitments team, working day to day with the engineers who build our Flex and Auto offerings. You'll own the analysis behind coverage targets and purchase recommendations, building on the usage forecasts from our forecasting service.

What You'll Do

• Analyze how usage forecasts become coverage targets and purchase recommendations, and work with Commitments engineers on how to improve them.
• Quantify risk and expected savings for each recommendation so customers and our team can trust the numbers.
• Analyze commitment performance across customers to find where our approach works and where it doesn't.
• Work with engineers to turn your findings into product changes, and measure their impact.
• Define how we measure recommendation quality, and report on it in terms the business understands.
• Explain your methods and results clearly to engineers, product, and customer-facing teams.

What We're Looking For

• 4+ years of experience as a data scientist, where your analysis shaped product or business decisions.
• Strong foundation in statistics, with experience turning forecasts into decisions.
• Fluency in Python and SQL, and comfort working with large, messy usage and billing datasets.
• Experience with optimization or decision-making under uncertainty.
• Experience working closely with engineers and product, and turning complex analysis into practical recommendations.
• Clear writing, and the ability to explain uncertainty to people who need to make a decision.
• Pragmatic, informed use of AI tools to speed up analysis and coding.

Nice to Have

• Experience with cloud pricing, reserved instances, savings plans, or committed use discounts.
• Background in finance, pricing, or risk modeling.
• Experience with machine learning methods.
• Experience designing experiments or causal analyses to measure the impact of changes.
• Experience working with large datasets on AWS.
• Familiarity with FinOps concepts.

Work Setup

Hybrid role based in New York City, with an office in Dumbo, Brooklyn

Team members typically work in the office 2–3 days per week

OR Remote US

Benefits

• Unlimited PTO
• 16 weeks of paid parental leave (birthing parents receive an additional 4 weeks at 50% pay)
• Two company-wide breaks per year: one around Labor Day and one at the end of the year
• Aetna Medical PPO plan with the majority of the premium covered by North
• Dental and vision insurance
• Flexible spending account (FSA) for health expenses and commuter benefits
• 30 day sabbatical every 4 years