Data in United States

About the Team The Applied organization brings OpenAI’s most advanced technology to the world through products like ChatGPT and the APIs that power a growing ecosystem of developer and enterprise applications. Data Engineering builds and operates the trustworthy, secure, and reliable data systems that power decisions across OpenAI. About the Role We’re looking for a Data Engineering Manager to lead the Growth & Revenue data engineering team. This leader will own the data strategy and execution for the data subject areas spanning growth accounting across all product surfaces, product partnerships, checkout, billing, payments, revenue, and monetization, helping OpenAI understand how people adopt, engage with, and pay for our products. You will partner closely with several Data Science, Business, and Engineering partners to connect product behavior to trustworthy subscriber, payment, and revenue measurement. In this role, you will: Build, manage, and grow a high-performing, inclusive team across the Growth & Revenue data subject areas. Define the data strategy for all the data subject areas you own. Deliver durable, well-modeled data products that connect product behavior, subscription state, checkout events, payment outcomes, and revenue. Establish trusted metric definitions and data quality standards so product, growth, finance, and executive leaders can make fast, consistent decisions. Partner with Data Science and Product teams to support experimentation, causal measurement, funnel analysis, and scalable self-serve analytics. Partner with Finance and Financial Engineering to ensure analytical revenue views reconcile to financial truth and production billing systems. Raise operational excellence for critical pipelines, including reliability, observability, privacy, governance, and incident response. Set a clear roadmap, make principled tradeoffs, and communicate progress and risk across technical and business stakeholders. You might thrive in this role if yo

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. Fraud Data is the data science and machine learning team within Plaid’s Fraud organization, responsible for using data and ML to improve and scale Plaid’s fraud products. Within Fraud Data, the Customer & Product Intelligence team focuses on understanding product performance, uncovering customer insights, and enabling go-to-market teams with data-driven solutions. The team partners closely with customers and GTM teams on fraud analyses and proofs of concept, turning customer learnings into scalable, reusable product capabilities. We also build the metrics, analytics, and data foundations that measure product health, identify opportunities for improvement, and guide product decisions across Plaid’s Fraud portfolio. As a Data Science Manager, you will lead a team responsible for customer-facing data science and Fraud product analytics. You will set the team's roadmap, develop its data scientists, and remain involved in analytical methods, technical reviews, and customer investigations. You will: Set a 6–12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team. Define product metrics, their underlying data, and reporting and

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

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE This is a sourcing-first role, not a deal-closing role. Baseten needs someone who can build and maintain deep relationships across the long tail of data center and powered land providers, well beyond the handful of large, well-known players that everyone in the market is already competing for. This coverage area is a key differentiator for Baseten's broader compute strategy, so we're looking for the best possible person in this specific lane rather than a generalist. You'll own the full lifecycle of a sourcing relationship — from first outreach to ongoing management — not just the introduction. WHAT YOU'LL DO Build and maintain a comprehensive map of data center and powered land opportunities, with a particular focus on the long tail rather than the handful of major, oversubscribed players Own the full sourcing lifecycle for each relationship — from identifying and reaching out to new providers, through negotiation support, to ongoing relationship management — not just the initial introduction Develop and manage sourcing relationships across neoclouds, hyperscalers, brokers, and independent operators Quickly and independently evaluate new sites and spaces to determine fit and priority Prepare business cases and cost analysis to support new data center and powered land opportunities, partnering with Finance where needed Maintain accurate records of suppliers, contracts, and commercial terms so the team has a reli

As a Senior Product Manager for Regulated Industries, you'll drive our compliance, data sovereignty, and new market presence roadmap—one of Datadog's highest-growth focus areas. You'll work cross-functionally with teams across GTM , Support, Corporate Development, and fellow product managers to help accelerate that growth. A key focus of this role is international expansion across strategic markets, alongside supporting our ongoing regulated industries initiatives. At Datadog, we place real value in our office culture—the relationships, collaboration, and creativity it fosters. We operate as a hybrid workplace so our Datadogs can build a work-life balance that fits them. What You'll Do Define the roadmap for delivering Datadog's platform to highly regulated customers, globally Collaborate with product managers to help them succeed in regulated markets Speak fluently to the technical details customers care about—data flows and security architecture—for both engineering and executive audiences Enable GTM by partnering closely with sales and marketing teams Partner with Compliance Engineering and InfoSec teams Work with marketing, sales, and post-sales teams to identify gaps in our regulated offerings Deliver AI capabilities responsibly to highly regulated customers Who You Are You have five or more years of experience in a SaaS/B2B regulated industries role—Product Management, Compliance, Global Public Sector Engineering, or Product Marketing You're passionate about working with customers in regulated markets such as public sector, healthcare, and financial services You're customer-focused with high standards for quality You're energized by growth-stage opportunities You can engage deeply with technical, compliance, security, and executive audiences alike—from platform engineers to CISOs and CTOs You have excellent verbal and written communication skills, with the confidence to present ideas to technical stakeholders and executives alike You enjoy partnering cro

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re hiring a Data Scientist to help build and scale our internal analytics capabilities. This is a foundational role where you’ll create dashboards, data models and insights to power business and product teams alike. You’ll collect requirements, define key metrics, and deliver insights directly to stakeholders. You'll define what success looks like across a technical, usage-based platform and turn ambiguous questions into analyses, forecasts, and experiments that shape Baseten’s product and strategy. RESPONSIBILITIES Build and maintain production-grade dbt models and dashboards across multiple functions with a focus on accuracy, simplicity and user experience. Define and instrument core metrics around ROI, product adoption, customer lifecycle, capacity, availability, revenue and costs. Ingest and transform raw data using tools like dbt, Airbyte, and BigQuery. Partner with Engineering, Finance, Marketing, and Sales teams to understand goals and translate them into data solutions REQUIREMENTS 5+ years of experience in analytics engineering, data analysis, analytics, data science or a related role Advanced SQL and dbt skills, with a record of building models, tests, semantic layers and lineage in a cloud data warehouse. Prior experience supporting complex cross-functional projects across GTM, Finance and Engineering across various stages of the customer journey. Experience building dashboards and self-serve analy

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 . We’re looking for a principal software engineer to lead the next generation of data infrastructure at Pinterest which powers mission critical big data and AI applications. You’ll be working on some of the most exciting big data and AI open source technologies (Flink, Spark, Kubernetes, etc.), at the scale of exabytes of data to help Pinners discover and do what they love. What you’ll do: Lead the strategy and technical direction of Pinterest’s data infrastructure for big data and AI applications Build and scale data infra frameworks and infrastructure to process petabytes-scale datasets, including compute engines, job management, resource management, scheduling and remote shuffling Work with internal customers on critical business use cases that rely on big data Provide thought leadership to the entire company on how data should be

About the Team OpenAI’s Industrial Compute team is building and productizing infrastructure capabilities that help organizations deploy and operate advanced AI systems at scale. The team works across AI hardware, systems engineering, physical infrastructure, and customer delivery to turn emerging technologies into reliable, repeatable infrastructure solutions. Our work sits at the intersection of technical strategy, product development, engineering, and deployment. We partner closely with customers and internal engineering teams to solve complex infrastructure challenges spanning compute, power, cooling, controls, and facility efficiency. About the Role We are seeking a senior, hands-on Data Center Infrastructure Architect to develop and optimize the physical infrastructure required for large-scale AI deployments. This is a broad technical role spanning data center architecture, electrical and mechanical systems, high-density compute, controls, telemetry, and digital modeling. You will use simulation, operational data, and digital-twin approaches to evaluate infrastructure designs, identify system-level constraints, and improve efficiency, reliability, cost, and speed of deployment. The ideal candidate can move fluidly between first-principles analysis, facility and equipment design, computational modeling, engineering review, and real-world implementation. You should be comfortable working across disciplines rather than operating solely within electrical, mechanical, or software boundaries. Key Responsibilities Define system-level architectures for high-density AI data centers across power, cooling, IT equipment, controls, and facility infrastructure. Develop digital twins and other computational models that represent the behavior of data center systems under changing workloads, environmental conditions, equipment configurations, and failure scenarios. Use design and operational data to identify constraints, improve PUE and related efficiency metrics, and optimize

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

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role: You will apply your expertise in statistical inference and experimentation to understand the impact of product changes and drive decision-making. You will explore ambiguous areas and conduct analysis to identify opportunities for the Growth org, helping shape the strategy and roadmap. You'll partner closely with product, engineering, and marketing leaders at every step of the development process, driving forward data science and analytics work. You'll work with your teams to determine north star and operational metrics, and build the foundational datasets and dashboards to monitor progress and make key decisions. You'll influence the broader company by communicating your findings and driving change in our product and business. (Insights are useful. Impact is even better!) Skills You'll Need to Bring: You are comfortable with ambiguity and motivated by business results. You have expertise in SQL and at least one scripting language (ideally Python or R). You know how to use statistical inference and experimentation to drive actionable recommendations. You are comfortable transforming raw data to build your own data sets

Data Architect, AI and Supply Chain Insights Description - Job Summary We are seeking a Supply Chain Data Architect who combines strong data architecture expertise with a data product mindset. The role is responsible for owning and evolving a portfolio of Data Products, designing scalable and reusable data models, and ensuring data assets are trusted, governed, and optimized for reporting, analytics, Data Science, Machine Learning, and AI use cases. The successful candidate will work closely with business stakeholders to understand processes, priorities, and opportunities, translating them into data strategies and architecture solutions that maximize business value and adoption. A strong understanding of data engineering concepts is foundational and required, including how data is acquired, transformed, and delivered across modern data platforms. The primary focus of the role is on data architecture, data modeling, data product maturity, business engagement, and AI ready design. Success is measured by the ability to create scalable, business ready data products that enable self service analytics, advanced insights, continuously leveraging the evolving AI technologies for our Supply Chain Stakeholder. The ideal candidate combines deep expertise in data architecture and modeling with business acumen, critical thinking, problem solving and a passion for innovation. They partner with business leaders, Data Engineers, Data Scientists, Product Owners, and AI practitioners to transform complex business challenges into data driven solutions Responsibilities Own and evolve a portfolio of Supply Chain Data Products, ensuring they are certified, compliant, governed, and aligned to the latest Data Governance standards while maximizing business value and adoption. Partner with busi

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. WHY DATA SCIENCE & ANALYTICS? The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product groups, we use this vast tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure the impact on our community of players and developers. WHY Consumer Apps? Roblox is used by tens of millions of people every day across a wide range of devices, including mobile, desktop, console, TV, and VR. The Consumer Apps team owns the app foundation that makes Roblox feel fast, fluid, and reliable for players and is dedicated to delivering superior performance, reliability, and user experience across all platforms Roblox supports. This team ensures a seamless and engaging user interface that facilitates intuitive interactions while enabling efficient, high-quality experiences

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 . The Data Product Platform is mission-critical to accelerate data-driven decision-making at Pinterest on the foundation of 100s of thousands of tables and an exadata-scale data warehouse. We strive to provide effortless, efficient, and reliable data products and platforms that power the entire company. We achieve this by investing in two core areas: Data Warehouse: Building and managing the foundational data warehouses that enable key analyses across both our core engagement and monetization products. Analytical Velocity: Creating agentic analytical tools that empower internal data users to leverage our vast data assets and capable infrastructure effectively. We are seeking a Staff Software Engineer to provide technical leadership and contribute to the development of solutions across both these pillars. In this role, you will shape the vision and

About Datadog: We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—allowing for seamless collaboration and problem-solving among Dev, Ops and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team: The Revenue Data Engineering Teams designs, builds and runs the data pipelines and helper systems to accurately and in a timely manner quantify our customers’ usage across all Datadog products. This team is at the leading edge of any new product we release. The Revenue Data Processing team builds and operates the data pipelines that does billing, and cost attribution for all Datadog products. We process terabytes of data daily to power revenue-critical systems and are at the center of every new product launch at Datadog. As a Senior Software Engineer, you will own meaningful parts of a large-scale, mission-critical processing platform — driving architectural improvements, building new billing capabilities, and maintaining the high reliability bar our downstream consumers depend on. You Will: Design and build high-throughput data pipelines for billing and cost attribution Drive platform improvements — latency reduction, Spark optimization, sharding, and cross-datacenter reliability Own root-cause investigations on billing accuracy issues in collaboration with Finance and Product teams Contribute to new billing features Work across Python and Scala, with technologies including Spark, Airflow, Trino, and Apache Iceberg Participate in on-call rotation and maintain a high reliability bar for production systems Contribute to engineering standards and help grow the technical culture of the team You Are: You have significant experience building and operating production data pipelines at scale using Spark and Airflow

About the team The Monetization Data Platform team builds the trusted data and platform foundations that power how the company develops, measures, and improves monetization products. We bring together product usage, pricing, billing, ads, payments, and financial data to help Product, Engineering, Finance, and GTM teams make better decisions and deliver reliable customer experiences. We work at the intersection of data engineering, product engineering, platform engineering, Finance, and GTM. Our goal is to turn complex monetization and financial data into accurate, explainable, and timely data products while building systems that scale with the growth and complexity of the business. About the role We are looking for a Data Engineer to improve and build the next generation of our monetization data platform. You will own high-impact systems end to end, from product instrumentation, source ingestion, and canonical modeling through quality controls, observability, and delivery to downstream consumers. This is a hands-on role for an engineer who enjoys solving ambiguous product and data problems, designing durable architectures, and partnering closely with Product Engineering, Finance, Accounting, and GTM. You will help define technical direction, raise the engineering bar, and turn monetization opportunities into trusted, scalable data products and platform capabilities. In this role, you will Design, build, and operate large streaming and batch data pipelines that process product, financial, and operational data from a variety of internal and external systems. Develop canonical data models and reusable data products for domains such as product usage, pricing, billing, ads, payments, revenue, and the general ledger. Establish strong guarantees for data accuracy, completeness, freshness, lineage, reconciliation, and auditability. Build frameworks and platform capabilities that improve developer productivity and make it easier for teams to launch, measure, and iterate on m