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North is building a next-generation cloud, AI, and data spend management platform that gives companies real-time visibility, control, and automation over their digital asset finances. The company helps customers save money by buying and managing cloud commitments on their behalf.
You'll join the Commitments team as a Data Scientist, working closely with engineers who build North's Flex and Auto offerings. Your core responsibility is owning the analysis behind coverage targets and purchase recommendations, building on usage forecasts from the forecasting service. Every recommendation directly impacts customer savings and commitment utilization—mistakes cost real money.
Key responsibilities:
- Analyze how usage forecasts translate into coverage targets and purchase recommendations, collaborating with Commitments engineers to improve them
- Quantify risk and expected savings for each recommendation so customers and internal teams can trust the numbers
- Analyze commitment performance across the customer base to identify where the approach works and where it needs refinement
- Partner with engineers to turn findings into product changes and measure their impact
- Define and report on recommendation quality metrics in business-friendly terms
- Communicate methods and results clearly to engineers, product, and customer-facing teams
The role is hybrid based in Dumbo, Brooklyn (2–3 days per week in office) or fully remote within the US.
REQUIREMENTS:
- 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 actionable decisions
- Fluency in Python and SQL; comfort working with large, messy usage and billing datasets
- Experience with optimization or decision-making under uncertainty
- Demonstrated ability to work closely with engineers and product teams, translating complex analysis into practical recommendations
- Clear writing and ability to explain uncertainty to decision-makers
- Pragmatic, informed use of AI tools to accelerate 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
- Machine learning methods experience
- Experiment design or causal analysis experience
- Large dataset experience on AWS
- FinOps familiarity
