Senior Applied Scientist (Finance)

TL;DR

Senior Applied Scientist (Finance): Building and operating production-grade forecasting systems for core financial metrics with an accent on revenue and bookings in a consumption-based business. Focus on developing reliable, explainable statistical models and ensuring operational trust for executive decision-making.

Location: Menlo Park, CA, USA

Salary: $156K – $224.2K

Company

A cloud data platform powering the era of the agentic enterprise through AI-native data solutions.

What you will do

• Own and improve production forecasting systems for core financial metrics, specifically revenue and bookings.
• Build scalable statistical and machine learning models translating customer behavior and usage patterns into forecasts.
• Design forecasting approaches prioritizing accuracy, stability, explainability, and operational trust.
• Establish high standards for model evaluation, backtesting, uncertainty quantification, and scenario analysis.
• Collaborate with Analytics Engineering, Finance, Sales, and Product teams to refine business drivers and forecast quality.
• Communicate forecast changes, risks, and model behavior to senior leadership.

Requirements

• Advanced degree in Statistics, Mathematics, Computer Science, or a related quantitative field.
• 5+ years of experience building production-grade statistical or machine learning systems.
• Deep expertise in forecasting problems (revenue, demand, or consumption) and proficiency in Python and SQL.
• Experience with large-scale data platforms such as hirify.global, BigQuery, Redshift, or Spark.
• Proven ability to manage high-stakes outputs for executive stakeholders and respond rapidly to production issues.
• Strong systems thinking regarding monitoring, validation, and anomaly detection.

Nice to have

• Experience with forecasting in consumption-based or hybrid SaaS business models.
• Experience with executive-facing financial planning systems.
• History of owning data products with daily production outputs.
• Experience mentoring other scientists and shaping modeling standards.