Snowflake28.04.2026
Senior Data Scientist
Полная занятостьUS-CA-Menlo Park
Обязанности
- 01Own and improve production forecasting systems for core financial metrics, especially current-quarter and longer-range revenue and bookings in a consumption-based business
- 02Build and maintain scalable statistical and machine learning models that translate customer behavior, usage patterns, ramps, renewals, and business context into actionable forecasts
- 03Design forecasting approaches that prioritize not only accuracy, but also stability, explainability, robustness, and operational trust
- 04Establish and maintain high standards for model evaluation, backtesting, forecast decomposition, uncertainty quantification, and scenario analysis
- 05Diagnose material forecast movements quickly and clearly, separating true business change from data issues, one-time events, timing shifts, and model artifacts
- 06Improve the reliability of the forecasting stack through better monitoring, anomaly detection, validation checks, change management, reproducibility, and lifecycle management
- 07Partner closely with Analytics Engineering and peer Data Scientists on shared infrastructure, upstream dependencies, and production processes across a complex forecasting system
- 08Work cross-functionally with Finance, Sales and Product to understand business drivers, incorporate high-quality business context, and improve forecast quality
- 09Communicate clearly with senior leaders on forecast changes, risks, and model behavior, especially in high-visibility or time-sensitive situations
- 10Raise the bar for technical rigor, production quality, and decision-making across the team through mentorship and technical leadership
Требования
- 01Advanced degree in Statistics, Mathematics, Operations Research, Economics, Engineering, Computer Science, or a related quantitative field, or equivalent practical experience
- 025+ years of experience building and operating production-grade statistical, forecasting, or machine learning systems with meaningful business impact
- 03Strong hands-on experience with forecasting problems, ideally in revenue, demand, supply, capacity, consumption, or other business-critical planning contexts
- 04Deep 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
- 05Strong proficiency in Python and SQL, with the ability to manipulate data, build models, and productionize analyses efficiently
- 06Experience working with large-scale data systems and modern data platforms such as Snowflake, BigQuery, Redshift, or Spark
- 07Demonstrated ownership of high-stakes outputs used by business or executive stakeholders, including experience responding quickly and effectively when something changes or breaks
- 08Strong systems thinking, including experience with monitoring, validation, anomaly detection, reproducibility, and safe model or pipeline changes in production
- 09Excellent communication skills, including the ability to explain complex forecast movements, uncertainty, and tradeoffs to senior business stakeholders
- 10A track record of leading through ambiguity, influencing cross-functional partners, and elevating technical standards across a team