Staff Finance Data Scientist – Consumption Forecasting

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San Francisco / $240000 - $300000 annum

INFO

Salary

SALARY:

$240000 - $300000

Location

LOCATION

San Francisco

Job Type
JOB TYPE

Permanent

Staff Data Scientist, Finance - 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
  • Establish backtesting, monitoring, and explainability standards that make forecast accuracy transparent and defensible
  • 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
  • Set forecasting best practices across the broader Data organization

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

CONTACT

Joshua Poore

VP Recruiting – Data Science, ML & AI

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