Senior Data Scientist

What You’ll Do

• Own and improve production forecasting systems for core financial metrics, especially current-quarter and longer-range revenue and bookings in a consumption-based business.
• Build and maintain scalable statistical and machine learning models that translate customer behavior, usage patterns, ramps, renewals, and business context into actionable forecasts.
• Design forecasting approaches that prioritize not only accuracy, but also stability, explainability, robustness, and operational trust.
• Establish and maintain high standards for model evaluation, backtesting, forecast decomposition, uncertainty quantification, and scenario analysis.
• Diagnose material forecast movements quickly and clearly, separating true business change from data issues, one-time events, timing shifts, and model artifacts.
• Improve the reliability of the forecasting stack through better monitoring, anomaly detection, validation checks, change management, reproducibility, and lifecycle management.
• Partner closely with Analytics Engineering and peer Data Scientists on shared infrastructure, upstream dependencies, and production processes across a complex forecasting system.
• Work cross-functionally with Finance, Sales and Product to understand business drivers, incorporate high-quality business context, and improve forecast quality.
• Communicate clearly with senior leaders on forecast changes, risks, and model behavior, especially in high-visibility or time-sensitive situations.
• Raise the bar for technical rigor, production quality, and decision-making across the team through mentorship and technical leadership.

What We’re Looking For

• Advanced degree in Statistics, Mathematics, Operations Research, Economics, Engineering, Computer Science, or a related quantitative field, or equivalent practical experience.
• 5+ years of experience building and operating production-grade statistical, forecasting, or machine learning systems with meaningful business impact.
• Strong hands-on experience with forecasting problems, ideally in revenue, demand, supply, capacity, consumption, or other business-critical planning contexts.
• Deep modeling skills, including strong judgment around when to use simpler driver-based approaches versus more advanced methods such as hierarchical, Bayesian, probabilistic, deep learning, or state-space models.
• Strong proficiency in Python and SQL, with the ability to manipulate data, build models, and productionize analyses efficiently.
• Experience working with large-scale data systems and modern data platforms such as Snowflake, BigQuery, Redshift, or Spark.
• Demonstrated ownership of high-stakes outputs used by business or executive stakeholders, including experience responding quickly and effectively when something changes or breaks.
• Strong systems thinking, including experience with monitoring, validation, anomaly detection, reproducibility, and safe model or pipeline changes in production.
• Excellent communication skills, including the ability to explain complex forecast movements, uncertainty, and tradeoffs to senior business stakeholders.
• A track record of leading through ambiguity, influencing cross-functional partners, and elevating technical standards across a team.

Especially Valuable Experience

• Forecasting in a consumption-based, usage-based, or hybrid SaaS business model.
• Experience with executive-facing financial forecasts or planning systems.
• Experience owning models or data products with daily or near-daily production outputs.
• Experience operating in environments where reliability, trust, and fast issue response matter as much as raw model performance.
• Experience mentoring other scientists and helping shape shared modeling or production standards.