What are the responsibilities and job description for the Staff Finance Data Scientist, Consumption Forecasting position at Harnham?
Staff Finance Data Scientist, Consumption Forecasting
Location: San Francisco or New York | Hybrid (3 days per week in office)
Salary: $240-300k base bonus equity (RSUs)
This is a rare chance to own forecasting infrastructure at the center of a high-growth, consumption-based developer platform, one that powers some of the world's most dynamic applications and scales with every developer and enterprise building on it.
As a consumption-based business, forecasting usage across compute, bandwidth, edge, and storage isn't a support function. It's foundational to how we plan infrastructure, revenue, and long-term strategy. This role exists to lead that work at the highest level.
What you'll own
This is a senior individual contributor role with organization-wide impact. You'll define forecasting methodology, build systems that scale with a rapidly growing platform, and sit at the intersection of Finance, Infrastructure, Product, and GTM with direct visibility to executive leadership.
- Own production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration from first principles to live system
- Build forecasting systems that account for usage-based pricing dynamics, consumption patterns, and customer lifecycle across the platform, built for how this business actually works, not retrofitted SaaS models
- Design hierarchical forecasting models across account, cohort, segment, and global aggregate levels, covering operational, quarterly, and long-range planning cycles
- Build scenario simulation frameworks to evaluate pricing changes, packaging adjustments, and product launches
- Partner with Finance on board-level reporting, with Infrastructure Engineering on capacity planning, and with Product and GTM on adoption curves and usage drivers
What we're looking for
- 7 years in data science, quantitative analytics, or applied statistics at senior or staff level
- Deep expertise in time-series forecasting and statistical modelling in a usage-based or SaaS environment
- Proven track record building and productionizing ML systems at scale
- Strong Python and SQL, with experience on large-scale usage and billing datasets
- Familiarity with probabilistic modelling, hierarchical forecasting, and causal inference
- Experience partnering with Finance or executive leadership on planning cycles
- Comfortable operating autonomously in fast-moving, ambiguous environments
Nice to have
- Background in cloud infrastructure, developer tools, or consumption-based revenue models
- Familiarity with modern data stacks: Snowflake, Delta Lake, dbt, Airflow
- Prior technical mentorship or informal leadership experience
Salary : $240,000 - $300,000