Data Analyst Jobs

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! The Data Platform team at Figma builds and operates the foundational systems that power analytics, AI/ML, and data-driven decision-making across the company. We serve a diverse set of stakeholders, including AI researchers, machine learning engineers, data scientists, product engineers, and business teams that rely on data for insights and strategy. Our team owns and scales critical platforms such as the Snowflake data warehouse, ML Datalake, orchestration and pipeline infrastructure, and large-scale data ingestion and processing systems, managing all data flowing into and out of these platforms. Despite being a small team, we take on high-scale, high-impact challenges. In the coming years, we're focused on building the data infrastructure layer for Figma's AI-powered products, driving cost and performance optimizations across our data stack, scaling our ingestion and reverse ETL capabilities for new product use cases, and strengthening data quality, reliability, and compliance at every layer. If you're passionate about building scalable, high-performance data platforms that empower teams across Figma, we'd love to hear from you! This is a full-time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Design and build large-scale distributed data systems that power analytics, AI/ML, and business intelligence across Figma. Develop batch and streaming solutions to ensure data is reliable, efficient, and scalable across the company. Manage and evo

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Instacart’s Shopping Experience team is focused on making it fast and effortless for customers to find the right items within a single retailer and complete their order with confidence. As a Senior Data Scientist dedicated to Search, you’ll own the analytics an

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Instacart’s Shopping Experience team is focused on making it fast and effortless for customers to find the right items within a single retailer and complete their order with confidence. As a Senior Data Scientist dedicated to Search, you’ll own the analytics an

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Credit Card business team's mission is to shape Robinhood’s vision in the credit and banking space by delivering smart, customer-focused financial solutions. Our team is dedicated to reshaping the credit landscape and redefining the way people interact with financial services daily. We leverage cutting-edge analytical tools and diverse datasets to build deep understandings of consumer credit behaviors. We aim to make financial services accessible to everyone, building programs that support Robinhood’s broader goals! As a Staff Data Scientist, you will build credit risk models that allow us to better serve our customers and make responsible lending decisions. Credit models are at the heart of all lending decisions. These models will drive decisions ranging from approve/decline, line assignment at origination and future credit limit increases. You will leverage traditional and non-traditional data sources to build highly predictive risk models. You will own the full lifecycle of model development from data prep, model building to model deployment. This role is based in our Menlo Park, CA, or Washington, DC office(s), with in-person attendance expected at least 3 days per w

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Data Engineering team builds and maintains the foundational datasets that power decision-making across Robinhood. We design reliable, scalable data systems that support product analytics, growth strategy, financial reporting, experimentation, and machine learning. The team partners closely with Product, Engineering, Data Science, and Finance to ensure accurate, well-modeled data is available to teams across the company. Our work directly influences how Robinhood measures performance, improves customer experience, and scales its products. As a Senior Data Engineer, you will design, build, and evolve core datasets that track product performance and company-wide metrics. You will develop scalable data pipelines that ingest application events and database snapshots into our data lake, ensuring high data quality and reliability. You’ll collaborate with application engineers to improve data generation patterns and with analytics teams to design intuitive, well-documented data models. This is an opportunity to shape the technical foundation that supports data-informed decisions across the organization! This role is based in our Menlo Park, CA office, with in-person attend

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions.We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Lyft Business builds products that help organizations move the people who matter most - employees, customers, patients, and guests - easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We are seeking a Senior Data Scientist to lead technical initiatives across the entire Lyft Business product suite. In this role, you will shape the technical vision, define algorithmic roadmaps, and drive execution for data science projects that accelerate growth, improve operational efficiency, and deliver measurable value to our enterprise partners. You’ll collaborate closely with Product, Engineering, Design, and Go-to-Market teams to build production ML models, experimentation frameworks, and advanced analytics that inform strategy and power product innovation. This is a high-visibility, high-impact role with direct influence on Lyft’s enterprise offerings. The ideal candidate will bring deep expertise in algorithm development, machine learning, causal inference, and experimentation, alongside strong business acumen in B2B contexts and a proven track record of t

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions.We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Lyft Business builds products that help organizations move the people who matter most - employees, customers, patients, and guests - easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We are seeking a Senior Data Scientist to lead technical initiatives across the entire Lyft Business product suite. In this role, you will shape the technical vision, define algorithmic roadmaps, and drive execution for data science projects that accelerate growth, improve operational efficiency, and deliver measurable value to our enterprise partners. You’ll collaborate closely with Product, Engineering, Design, and Go-to-Market teams to build production ML models, experimentation frameworks, and advanced analytics that inform strategy and power product innovation. This is a high-visibility, high-impact role with direct influence on Lyft’s enterprise offerings. The ideal candidate will bring deep expertise in algorithm development, machine learning, causal inference, and experimentation, alongside strong business acumen in B2B contexts and a proven track record of t

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As the Engineering Manager for the Lakehouse Foundation team, you will lead a group of engineers responsible for the foundational data layer that all of Lyft's data systems and emerging AI workloads are built on. The team owns catalog and metadata management, table formats and storage, and the access patterns and gateways through which other engineering teams interact with Lyft's data. As Lyft converges on a unified lakehouse architecture, this team builds and operates the single source of truth that powers analytics, machine learning, experimentation, and every business decision made from data. You will play a key role in shaping the team's technical direction, partnering with peer Data Platform teams on a multi-year platform evolution, and developing engineers who operate with autonomy on systems of significant scale and complexity. Lyft's Infrastructure teams build the foundational systems that the rest of engineering depends on to move fast, ship reliably, and scale efficiently. These are high-leverage roles where the work you and your team do has a multiplicative effect across the company. We're looking for experienced leaders who can balance the discipline of operating critical infrastructure with the curiosity to keep evolving how Lyft builds. Engineering at Lyft is a place where managers and engineers operate with high ownership and strong technical judgment. Our engineers expect their managers to be honest, available, and focused on the work that matters: developing their teams, removing obstacles, and giving people the support they need to do their best work. We build teams that are inclusive, technically rigorous, and have a strong sense of ownership for what they build. Responsibilities: Lead a team responsible for Lyft's foundational data layer, including catalog and metadata management,

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Capital team is responsible for managing the end-to-end risk strategy for Stripe's lending product. The team is based in the US and Canada, and is composed of curious, driven, and analytical individuals who are passionate about using their skills to shape the future of Stripe. We partner closely with Stripe's engineering, data science, product, and servicing teams to leverage existing platforms, integrate industry best practices, and develop novel solutions to evaluate and manage credit risk. If you are interested in joining a fast-growing organization and applying your experience to shape the future of Stripe, we encourage you to apply. What you’ll do As a key member of the Capital team, you will have the opportunity to shape the future of Stripe's credit policy by driving meaningful changes to the risk and underwriting framework. You will leverage Stripe's vast data assets to formulate your recommendations and work closely with our partners and, where applicable, leverage third-party data. We are a small and lean team, which means you will have the autonomy and the responsibility to manage end-to-end risk initiatives. Responsibilities Architect and implement credit policies based on Stripe's proprietary data and selected industry data to target, price, and size capital products. Utilize your analytical and technical skills to provide credit risk recommendations, deliver insights, and support strategic business decisions. Collabor

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Capital team is responsible for managing the end-to-end risk strategy for Stripe's lending product. The team is based in the US and Canada, and is composed of curious, driven, and analytical individuals who are passionate about using their skills to shape the future of Stripe. We partner closely with Stripe's engineering, data science, product, and servicing teams to leverage existing platforms, integrate industry best practices, and develop novel solutions to evaluate and manage credit risk. If you are interested in joining a fast-growing organization and applying your experience to shape the future of Stripe, we encourage you to apply. What you’ll do As a key member of the Capital team, you will have the opportunity to shape the future of Stripe's credit policy by driving meaningful changes to the risk and underwriting framework. You will leverage Stripe's vast data assets to formulate your recommendations and work closely with our partners and, where applicable, leverage third-party data. We are a small and lean team, which means you will have the autonomy and the responsibility to manage end-to-end risk initiatives. Responsibilities Architect and implement credit policies based on Stripe's proprietary data and selected industry data to target, price, and size capital products. Utilize your analytical and technical skills to provide credit risk recommendations, deliver insights, and support strategic business decisions. Collabor

About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with

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. Principal Data Cloud Architect - SI Partners We are seeking a highly experienced and results-driven AI/ML focused Principal Data Cloud Architect to join our Partner Solution Engineering (PSE) team. Our mission is to empower System Integrator (SI) partners to rapidly achieve technical wins and successful production deployments of AI/ML solutions on the Snowflake AI Data Cloud. Snowflake, the AI Data Cloud, enables teams to seamlessly run analytical workflows, develop agentic apps, and train models using both structured and unstructured data. With over 4,000 customers leveraging our gen AI and ML technology weekly, we are at the forefront of AI innovation. This role is crucial in accelerating AI/ML customer journey technical wins and production deployments being implemented by SI partners. IN THIS ROLE YOU WILL PERFORM: Strategic Account Alignment with top accounts for SI partners (Focus on Acceleration): Unlock High-Impact Customer Journeys: Identify and prioritize AI/ML customer journeys for SI partner top accounts, focusing on quick wins and high consumption, informed by your understanding of SI partner needs. Expedited POCs and RFPs: Provide support for partners during RFI/RFP processes and POCs, ensuring rapid turnaround and successful outcomes, informed by your SI propo

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 enhanc

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. At the center of the data cloud is the Snowflake Database Engineering team. We are responsible for building the core query engine used to process the massive amounts of diverse data managed by our customers. A core part of the Database Engineering group is the Query Language team which is responsible for designing, developing, and maintaining core SQL features, including advanced analytics, scripting, and the developer experience. We are seeking a Senior Engineering Manager to own and drive the effort to build core database capabilities to serve agentic workloads. You'll set the technical direction, build and grow the team behind it, and shape how the core engine and the SQL language evolve to serve this new class of workload. It's a rare chance to lead a foundational bet at the exact moment the industry is racing to solve it, with the scale, customer base, and platform to make your work matter to millions of queries a day. If you want your fingerprints on how the world's data platforms adapt to the age of AI agents, this is one of the best seats in the industry. AS A SENIOR ENGINEERING MANAGER AT SNOWFLAKE, YOU WILL BE EXPECTED TO: Drive the evolution of core database and SQL capabilities to serve emerging AI and agentic workloads alongside traditional analytics Lead and g