Data Scientist, Finance Forecasting

Responsibilities

• Own a core part of the modeling work, including production revenue forecasts or causal measurement for launches and events.
• Develop, deploy, monitor, backtest, and improve production models.
• Build accuracy tracking and establish a cross-methodology accuracy baseline as a standing Finance metric.
• Research event-aware forecast architectures, hierarchical reconciliation, and causal designs for launch-driven changes.
• Translate model outputs and accuracy results into recommendations for Finance and executive leadership.
• Partner with the Analytics Engineer on feature pipelines, model deployment, and the forecast store.

Requirements

• Substantial experience in data science, forecasting, or quantitative finance, including ownership of production models.
• Deep fluency in Python and SQL and experience productionizing analytical work.
• Strong applied statistics foundation, with depth in either production time-series methods or causal inference.
• Experience with backtesting and accuracy tracking.
• Experience presenting and defending forecasts or causal estimates to executives.
• Bias for action and comfort working in ambiguous, early-stage environments.
• Bachelor's degree or equivalent combination of education, training, and experience in a relevant field.

Preferred Qualifications

• Experience with exogenous-regressor or event-aware forecasting.
• Familiarity with hybrid or foundation-model forecasting systems such as TimeGPT-class systems.
• Background in pricing and elasticity modeling or marketing-mix modeling.
• Experience forecasting consumption-based or usage-billed businesses.

Compensation and Benefits

• Annual salary range: $265,000–$320,000 USD.
• Competitive compensation and benefits.
• Optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours.
• Office space for collaboration.