Data in United States

Databases and data stores are at the center of our applications, for legacy applications and modern AI applications alike. Yet most observability and optimization approaches lack a holistic approach or application context. Datadog has been on a mission to revolutionize how databases are operated, flipping what is often seen as a black box of complexity prone to security and performance risks, into a well oiled machine enabling our builders and businesses to move faster and smarter. We’re looking for an experienced product manager passionate about joining this mission to lead this product opportunity. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead ambitious investments that rethink how customers operate and get value from their databases, diving into ambiguity, working with our customers on new models, and shipping new products and changes to existing products. Develop a deep understanding of our customers and their issues, what problems are really behind those issues, and how we can improve how databases are operationalized across SRE teams, DBAs and application developers. Continuously refine your understanding of database management systems and datastores from SQL and OLTP based to NoSQL e.g. AWS RDS, PostgreSQL, SQL Server, MongoDB, MySQL, etc Define, build and launch the next generation of database monitoring and optimization capabilities for our customers Join a talented engineering team with a record of disrupting observability approaches to further the mission of demystifying and optimizing databases using your team’s creativity, alongside your customers’ problems, as a key resource. Collaborate with other Product teams in Datadog to maintain and improve all Datadog products, improve the seamless integration across th

Today, everyone from PMs to Sales to SREs uses AI to query their business data - but every answer is a one-off with no governance, no consistency, and no visibility for data teams. We're building the system that fixes this: a context layer that learns from existing data tools driving high quality and consistent answers, an AI-powered query experience, full governance for data teams, and rich analysis surfaces to present and share the results. You'd be building a zero to one product of what we believe will become a major new product line for Datadog. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What you'll do Drive the product vision and roadmap spanning the Data agent experience, the semantic/context layer, governance console, chat experience and analysis surfaces (dashboards, notebooks, sheets) Own the end-to-end product lifecycle from discovery to launch, working with a cross-functional team of engineers, designers and other PMs Deeply understand the needs of two key personas: data teams (who govern and curate) and data consumers (PMs, engineers, SREs, executives who ask questions) Design the context and governance layer that makes AI-powered analytics trustworthy - including auto-generation from existing BI tools, eval frameworks, confidence scoring, and self-improvement loops Define how observability data and business data come together to serve unique use cases Engage directly with early customers and internal dogfooding users to iterate on accuracy, usability, and trust Independently research the competitive landscape across legacy BI vendors, warehouse-native analytics, AI-first startups, and AI labs Work on the product pricing Work with GTM teams to define positioning, packaging, and the path to displacing entrenched tools Who you are 5+ years of experience

Datadog's Forward Deployed Engineering function is in an active growth phase, and the FDE Lead will play a central role in shaping what comes next. Working in close partnership with the Head of Datadog for Startups and Forward Deployed Engineers, and the existing FDE team, you will help define and expand the FDE framework, build out the structures and processes that allow the team to operate at scale, and extend the program's reach well beyond any single customer segment. This role sits at the rare intersection of sales, execution, program design, and hands-on engineering leadership. You are part field technical leader, part program architect, and part cross-functional connector. You will help determine what the FDE motion looks like at Datadog, contribute to its playbook, and push the boundaries of what the team can deliver. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Evolve and scale the FDE operating model end to end: engagement intake, scoping, sprint delivery, handoff back to account teams, and the success metrics (time-to-value, adoption lift, ARR influence, NPS) and reporting infrastructure that support them. Build out a catalog of FDE offerings spanning observability quickstarts, custom integration development, LLM/AI observability accelerators, CI/CD pipeline instrumentation, and cost optimization deep dives, and contribute to their pricing and business models, including free-to-paid conversion plays, paid deployment packages, and post-deployment success motions. Capture product and feature gaps uncovered during deployments, translate them into structured prioritized briefs, and partner with PM and Engineering to strengthen the field-feedback channel that informs roadmap decisions on a regular cadence. Hire, onboard, an

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

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 Staff Software Engineer to help build the next generation of Pinterest’s big data storage platform. You’ll work on some of the most exciting big data open source technologies — especially Apache Iceberg — at exabyte scale to power the data infrastructure that helps Pinners discover and do what they love. As a Staff Software Engineer, you’ll serve as a technical leader and hands-on contributor, designing and building highly scalable storage systems for Pinterest’s data lake. You’ll partner closely with teams across data, ML/AI, analytics, and infrastructure to evolve our storage and metadata management capabilities, enabling efficient, reliable, and governed access to data at massive scale. What you’ll do: Design, implement, and optimize Pinterest’s exabyte-scale data lake storage platform. Lead complex technical projects and

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 accelerating 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 three 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 powerful analytical tools that empower internal data users to leverage our vast data assets and capable infrastructure effectively. Data Governance: Defining and implementing the data governance policies and tools necessary to ensure the responsible, efficient and compliant storage and handling of all data. We are s

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 . This role focuses on advancing the science and systems behind ML measurement, feature understanding, and causal inference at scale. The work spans areas such as production feature importance platforms, observational causal estimation in Pytorch, large-scale proxy metric development, and data-driven approaches to ML infrastructure efficiency. We're looking for an enthusiastic individual contributor to perform high-impact technical work across this space. This person will drive foundational innovations, own the end-to-end design of production ML systems, establish rigorous methodological standards, and partner cross-functionally to turn successful research into durable platform capabilities that raise the ceiling for the entire ML organization. What you’ll do: We are looking for an experienced and highly capable Data & Applied Scientist

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 brings millions of people the inspiration to create a life they love. Behind that experience is a complex infrastructure ecosystem that powers reliability, performance, measurement, and efficiency across the platform. As Pinterest grows, it’s increasingly important that we understand these systems clearly so we can make smarter decisions for both Pinners and the business. We’re looking for a Data Scientist to join our Infrastructure Data Science team. In this role, you’ll partner with engineering and cross-functional teams to make Pinterest’s infrastructure more measurable, intelligible, and actionable. Depending on the area, your work may span app performance, shopping infrastructure, metrics quality, infrastructure governance, or site reliability. You’ll help build the data foundations, measurement systems, and analytical fram

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 Our backend systems power the clients used by millions of customers every year to buy their groceries online. These systems must also support tight integration with the largest retailers in the US and Canada. Engineering at Instacart provides the opportunity to work on challenging scaling problems while also designing the features that will define our industry. You will learn how to build in an open collaborative environment serving millions of requests daily. Finance data engineering is part of the Data Infrastructure team, working closely with accounting, billing & revenue teams to support the monthly/quarterly book close, retailer invoicing and internal/external financial reporting. The team plays a critical role in defining how financial data is modeled and standardized for uniform, reliable, timely and accurate reporting. This is a high impact, hi

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: MarTech Data Science Measurement empowers Airbnb to optimize marketing ROI by generating data-driven recommendations. We lead the way in defining and advancing best practices for measuring and optimizing marketing impact. We collaborate with Marketing, Finance, and Engineering to provide actionable recommendations and tools based on effective, timely, and granular measurements. Our team’s tenets are: Actionable: Deliver insights that drive confident business decisions. Impactful: Prioritize projects based on their expected value to Airbnb. Balanced: Adapt methods to business questions and data realities, acknowledging limitations. Rigorous: Maintain methodological integrity and quantify the sensitivity of findings. Innovative: Invest in advancing measurement science and developing new methods. Influential: Share learnings across Airbnb and the broader data science community. The Difference You Will Make: We are seeking an experienced (Contract) Sr. Data Scientist for a 24 month contract with deep expertise in marketing measurement, with a particular focus on Marketing Mix Modeling (MMM) and geo-based causal inference. The ideal candidate brings strong statistical intuition and hands-on modeling experience to quantify the incremental impact of Airbnb's marketing investments across channels and geographies. They are fluent in Python, comfortable working with Bayesian frameworks, and can translate complex measurement findings into clear, actionable recommendations for senior stakeholders. A Typical Day: Marketing Mix Modeling: Design, build, and maintain MMM models that est

About the Team OpenAI’s Agentic Data Science team helps shape how AI agents are built, deployed, and improved across our products. We partner with product, engineering, research, and security teams to define meaningful measures of success, understand how our systems behave in the real world, and translate evidence into better decisions. As AI agents become more capable, they can write and execute code, access sensitive systems, and complete increasingly complex tasks with greater autonomy. These capabilities create powerful opportunities to improve cybersecurity, but they also introduce risks that traditional security tools and processes were not designed to address. Meeting this moment requires new ways to measure security, evaluate defenses, and distinguish genuine risk reduction from friction that slows users down. About the Role We are looking for a senior data scientist to help define what effective cybersecurity looks like in the age of AI agents. You will work across OpenAI’s Security organization and cybersecurity product teams to measure emerging risks, improve internal security controls, and shape AI-powered security products. The problems are foundational: How do we know whether an agent’s security controls are effective? Which safeguards meaningfully reduce risk, and which create unnecessary friction? When an AI system identifies a potential vulnerability, how do we determine whether the finding is accurate, actionable, and ultimately resolved? How do we detect anomalous behavior or risky access when the systems themselves are changing rapidly? You will report into Data Science while partnering closely with Security, Cyber Product, Engineering, and Research. This is a high-ownership role for someone who can establish a new analytical discipline, operate across organizational boundaries, and turn ambiguous security challenges into measurable improvements. In This Role You Will Define how we measure AI-agent security. Establish metrics and evaluation frame

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! Prior to applying please note: W e are currently unable to provide visa sponsorship for this position (including H-1B, OPT, F1, CPT or other employment-based visas). Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. This role is hybrid requiring 2 days in office at our San Francisco hub every Tuesday & Wednesday (located at 130 Sutter St, San Francisco, CA). About the Role Data Science plays a crucial role in driving impact at Taskrabbit. As a member of the team, you will help drive our business strategy forward through predictive insights. We are seeking a highly skilled and motivated Staff Data Scientist to join us, working closely with cross-functional teams from product, finance, engineering, risk and operations to provide data-driven insights and solutions that enhance our products and accelerate growth while minimizing marketplace losses.

About the Team The GTM Intelligence Solutions team builds the data and decision systems that help customer-facing teams take the right action at the right time. We combine product telemetry, commercial data, customer context, and field activity to identify account health and opportunity, recommend actions and use cases, deliver intelligence through field-facing products and agent workflows, and measure what happens next. We’re looking for a Data Scientist to help build the next generation of GTM intelligence at OpenAI. You will own a flexible portfolio of high-impact decision data products and work closely with Technical Success and other GTM teams to ensure the work drives better decisions. About the Role As a Data Scientist on GTM Intelligence Solutions, you will define and build the intelligence systems that help customer-facing teams prioritize accounts, identify risks and opportunities, choose interventions, and understand what worked. You will set the roadmap and methodology, build canonical features, ship reliable production workflows, monitor quality and adoption, and improve the systems using field feedback and business outcomes. This role combines hands-on technical depth with strong product and business judgment. You should be as comfortable writing production Python and advanced SQL, defining durable data contracts, and operating decision products as you are evaluating a ranking approach or designing an experiment. You will personally ship reliable first versions and partner with Analytics Engineering and Data Engineering when work requires shared infrastructure or additional scale. In This Role, You Will Set the roadmap and methodology for GTM intelligence and decision products, using deep stakeholder discovery to probe beyond stated requests, uncover the underlying decisions, workflows, constraints, and measures of success, and translate them into measurable systems. Own the full lifecycle of intelligence products, including feature definition, methodo

About the Role OpenAI's ads platform is experiencing rapid global scale. As the Lead Data Scientist for SMB Ads Growth, you will architect the analytics function end-to-end—driving strategy across targeting, funnel optimization, and performance forecasting. You will work directly with the SMB Ads Marketing team and your insights will be the primary catalyst for high-stakes decisions across marketing, product, and sales engineering. What You'll Do Full-Funnel Analytics Establish the foundational growth metrics and North Star KPIs for the SMB Ads ecosystem, optimizing the journey from lead acquisition to long-term retention. Diagnose funnel friction points through advanced behavioral analysis and quantify the incremental revenue impact of proposed optimizations. Partner cross-functionally to transform complex data findings into actionable, high-priority roadmaps for product and marketing stakeholders. Targeting, Segmentation & Propensity Modeling Engineer sophisticated propensity models and look-alike frameworks to identify and capture high-LTV SMB advertisers. Own the lifecycle of target list construction, including advanced data enrichment, multi-dimensional prioritization, and granular performance tracking. Develop robust segmentation architectures that power hyper-personalized outreach across paid, partnership, and outsourced (BPO) channels. Synthesize market signals to refine our value proposition, ensuring OpenAI remains a key platform for SMB business growth. Campaign Analytics & Measurement Design and implement rigorous multi-touch attribution and incrementality frameworks to evaluate channel efficacy. Lead the experimental roadmap: formulate hypotheses, execute A/B and multivariate tests, and communicate results to executive leadership. Automate business-critical reporting and dashboards to provide real-time visibility during weekly operating reviews. Forecasting & Planning Build high-fidelity revenue and advertiser growth models to project perfor

About the Role OpenAI's ads business is scaling quickly. As the Data Scientist for Ads Demand, you will build the measurement and insight foundation for understanding demand health and advertiser value across the marketplace. You will partner closely with Ads Sales leadership and Ads Product leadership—along with Marketing Science and product and sales teams—to diagnose advertiser performance, define benchmarks, identify growth opportunities, and turn advertiser feedback into product priorities. Your work will shape demand strategy, improve advertiser outcomes, and help OpenAI build for its most valuable advertisers. What You'll Do Demand Health & Measurement Define the North Star metrics, diagnostic framework, and measurement strategy for demand health across the ads system. Build the operating view of demand across spend, active advertisers, retention, budget utilization, delivery, concentration, and mix; identify emerging risks and opportunities. Diagnose changes in demand through cohort analysis, decomposition, experimentation, and causal methods, translating findings into clear actions for Sales and Product leadership. Advertiser Performance & Benchmarks Own the end-to-end view of advertiser outcomes—including delivery, ROAS, conversion performance, retention, and budget efficiency—for individual advertisers and key cohorts. Establish actionable benchmarks by objective, vertical, advertiser size, geography, maturity, and product adoption, with statistically sound peer comparisons. Develop early-warning signals and opportunity scoring that help sales teams surface under-delivery, performance risk, and advertiser growth potential. Set standards for metric definitions, data quality, and interpretation so leaders can separate real marketplace changes from seasonality, selection effects, and measurement artifacts. Insights, Adoption & Advertiser Feedback Partner with Marketing Science, Sales, and Product to translate analysis into credible advertiser-fac