Senior Data Scientist

Senior Data Scientist

Snowflake

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. ABOUT THE TEAM The Finance Data Science team owns the forecasting systems that power Snowflake’s financial planning, operating cadence, and long-term strategy. Our work informs executive decision-making, corporate planning, investor reporting, and cross-functional decisions across Finance, Sales, and Product. We build and operate production forecasting systems for Snowflake’s core money-in metrics, with a particular focus on revenue and bookings in a consumption-based business. Our forecasts are highly visible, widely used, and foundational to how the company plans and operates. This is a high-trust team operating at the intersection of statistical modeling, production systems, and financial decision-making. THE ROLE We are hiring a Senior Applied Scientist to own and advance mission-critical forecasting systems used across the company. This role is not just about building models. It is about developing reliable, explainable, production-grade forecasting systems that leaders can trust to make decisions. You will work on high-impact, open-ended problems involving revenue forecasting, customer consumption behavior, workload ramps, renewals, and other leading indicators that feed Snowflake’s broader financial planning processes. You will partner closely with Finance, Sales, Product, and Analytics Engineering to improve forecast accuracy, stability, and operational trust. This role is well suited for someone who combines strong modeling depth with production rigor, strong business judgment, and a high sense of ownership. 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. WHAT SUCCESS LOOKS LIKE In this role, success means you can build and operate forecasts that are not only technically strong, but trusted, stable, and decision-useful. You know how to balance modeling sophistication with business practicality. You can move quickly when forecasts change, communicate clearly about why they changed, and improve the system over time so that it becomes more reliable and more trusted. Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

Senior Data Scientist - Product

Snowflake

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Product Data Science team is looking for a Full-stack Senior Data Scientist to come aboard and be part of Snowflake’s most critical initiatives. In this role, you will work closely with our Product and Engineering teams on everything from core operations, to innovative AI/ML tools, to our fastest-growing new and experimental features. You will work on long-running analytical initiatives yielding substantial product enhancements. This is a strategic, high-impact role that will help shape the future of Snowflake products and services. PLEASE NOTE: The position level is determined during the interview process and is influenced by various factors, including experience, educational attainment, skill level requirements, and overall interview performance. AS A SENIOR FULL STACK DATA SCIENTIST AT SNOWFLAKE YOU WILL: * Be a proactive partner to Product Management and Engineering to shape feature roadmaps and help design metrics and analytical workflows to evaluate their success and effectiveness.   * Build efficient data models and high quality production pipelines and partner with Engineering for all necessary telemetry.  * Build scalable and extensible analytics/ML/causal inference frameworks to uncover feature usage patterns, subtle issues with the system, potential performance enhancements, and areas to improve customer experience. * Be an early adopter/pro user of Snowflake features and provide feedback on design parameters.   * Evaluate the right surface (Snowflake Notebook/Worksheet/Snowsight Dashboards/Streamlit Apps) to disseminate your insights for maximal impact.  * Influence decisions and drive initiatives with the Product Management and Engineering teams to drive better outcomes for our customers. * Answer questions from the executive team for reporting to the board and contribute to industry reports and similar publications. * Think creatively and be scrappy to find optimal solutions to our complex, often unstructured problems. OUR IDEAL CANDIDATE WILL HAVE: * MS/Ph.D. in quantitative discipline (Math, Statistics, Operations Research, Economics, Engineering, or CS).  * 8+ years of relevant data science or related experience.     * Expert-level experience working with SQL & Python including scikit-learn, numpy, and pandas. * Expert in working with large-scale machine generated data (e.g., logs, application telemetry, or customer usage data). * High fluency with MPP databases, such as Snowflake, Redshift, BigQuery, Vertica, etc.  * Expert data-driven storytelling skills to convey insights to business leaders and technical stakeholders and influence decisions.  * The ability to thrive in a dynamic environment, being flexible and willing to jump in and do whatever it takes to contribute to the success of your area. Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

Senior Data Engineer - Product

Snowflake

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a skilled Snowflake Data Engineer to join our Product and Data Science team. The ideal candidate brings a solid background in data engineering, with deep expertise in Snowflake and cloud technologies. In this role, you will design, build, and maintain robust data pipelines, ensuring our data infrastructure is scalable, reliable, and efficient. You will partner closely with product and data scientists, providing tools, automation, and best practices to accelerate their work, improve data quality, and ensure consistency across pipelines and dashboards. Additionally, you will play a critical role in cost optimization for data operations, owning efficient data modeling and pipeline performance. This position is also key in building and scaling our enterprise data warehouse, helping to shape the future of our data ecosystem. Responsibilities * Design, develop, and maintain scalable data pipelines using Snowflake and cloud technologies. * Own and manage cost optimization for Product and Data Science team operations. * Optimize pipelines for performance, reliability, and efficiency. * Build and maintain dashboards and reporting platforms using Streamlit. * Collaborate with cross-functional teams to gather requirements and deliver robust data solutions. * Work with modern AI tools, including Cursor, to accelerate development. * Implement data governance, security best practices, and access control policies. * Develop and enforce data quality checks, SLA monitoring, and dependency tracking. * Utilize version control systems (e.g., Git) and manage deployment workflows. * Proactively troubleshoot and resolve data-related issues. Qualifications * Bachelor’s degree in Computer Science, Engineering, or a related field. * Proven hands-on experience with Snowflake, including data modeling, ETL/ELT development, and performance tuning. * Advanced proficiency in Python, with experience scripting and automating data workflows. * Proven experience working with Spark for large-scale data processing. * Demonstrated experience building Streamlit applications integrated with Snowflake. * Strong command of SQL for complex data querying and analysis. * Familiarity with cloud platforms such as AWS, Azure, or GCP, and services like S3, Redshift, or BigQuery. * Strong problem-solving and communication skills. * Ability to thrive both independently and as part of a collaborative, fast-paced team environment. Preferred Qualifications: * Master’s degree in Computer Science, Engineering, or a related discipline. * Strong understanding of data warehousing principles, architecture, and best practices. * Experience working within Agile development frameworks (e.g., Scrum, Kanban). Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com