Data Scientist, Finance

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is seeking an experienced Staff Data Scientist to join our Finance & Business Operations team. This is a hybrid data-science / applied-AI / product-engineering role inside Pinterest's CFO organization. It sits at the intersection of forecasting and finance analytics, internal tool-building, and AI adoption — and the person in it is expected to operate across all three. The core mandate is to make the CFO org's forecasting and planning work faster, be more rigorous, and more self-serve. In practice that has meant owning a forecasting product end to end (data pipeline through user-facing UI), partnering directly with Finance, BizOps, and Core/Monetization stakeholders to embed it in their workflows, and turning the company's emerging AI platform capabilities into tools that finance teams actually use day to day. This is a high-

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. Staff Data Scientist, Finance About the Team The Finance Data Science team builds the forecasting and decision systems that power Snowflake's financial planning, operating cadence, and long-term strategy. Our work informs executive decision-making, product and go-to-market priorities, resource allocation, pricing, and cross-functional decisions across Finance, Product, Sales, and Data Science. We are expanding a driver-based revenue modeling platform that translates product and workload activity into trusted financial outcomes. The program began with one product category and will scale a common modeling and publishing framework across Snowflake's product categories. The models are highly visible, refreshed frequently, and designed for self-service scenario planning and business reviews. The Role We are hiring a Staff Data Scientist to lead the next phase of Snowflake's driver-based revenue modeling program. This role is not just about building models. It is about creating reliable, explainable, production-grade decision systems that connect upstream business and product levers to revenue outcomes. You will own high-impact, open-ended problems spanning driver identification, revenue decomposition, leading indicators, cohort and use-case modeling, scenario analysis, and multi

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 revenue planning and long-term financial strategy. Our work supports corporate planning, executive decision-making, and investor reporting, and we partner closely with Product and Sales to understand customer behavior and product impact. We operate at the intersection of machine learning, statistical research, and corporate finance, building production-grade forecasting infrastructure that is foundational to how the company plans and operates. The Role As a Senior Data Scientist, you will independently lead high-impact modeling initiatives and build production-ready forecasting systems for core financial metrics. You will work on complex, open-ended problems at the intersection of machine learning and business strategy, translating real-world financial questions into rigorous, scalable models. What You’ll Do Design and implement advanced time-series and probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches, multivariate forecasting). Contribute to internal tooling and shared infrastructure that enables scalable forecasting and analytics. Establish best practices for model evaluation, backtesting, uncertainty quantification, and scenario simulat

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, Pr

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners. As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features. Responsibilities: Work at the intersection of product analytics, machine learning, and fraud a

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Senior Data Scientist - Network Value (Credit) The Network Value Data Science team is helping Plaid build an industry-leading fintech consumer network with best-in-class products and user experiences. We are a product analytics team embedded in key product areas across Plaid. We support some of Plaid’s most important OKRs and help execute on product roadmaps. We translate ambiguous product questions into tractable analysis, serve as analytical thought partners throughout the org, identify opportunities to build better products, and champion a data-first decision-making approach everywhere we go. You’ll be a Data Scientist supporting Credit, a critical product area within Plaid’s Network Value portfolio. You’ll become a data and analytical thought partner to product managers, engineers, and cross-functional stakeholders, helping shape Credit product strategy, improve product performance and user experience, and grow Plaid’s consumer network. You’ll translate business questions into analytics projects, perform ad-hoc and strategic analysis, improve visibility into core systems through data modeling and dashboarding, create OKRs and KPIs tied to business goals and user experiences, a