Data Analytics Partner in United States

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

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Senior Analytics Engineer, you’ll be responsible for laying the foundation for a best-in-class analytics function. You’ll partner closely with our data science team and business stakeholders to ensure that our analytics stack and processes meet the business needs today with an eye towards the future. What you’ll do as an Senior Analytics Engineer at Vanta: Design and implement complex data models to enable dashboards, self-serve analytics, and data science teams. Write highly tuned, scalable SQL queries running over large-scale, heterogeneous data warehouses. Enable AI tooling with semantic layers and observability, guiding analytics functions on best practices. Manage and improve data infrastructure needed to drive data-driven decision-making solutions. Help develop front end applications to expose analytical data sets enterprise wide Work with the Product and Corporate Engineering system teams to structure source systems for reporting consumption across the enterprise. How to be successful in this role: Have at least four years of experience working with data and two years of experience in Software Engineering or a related field. Have experience with common analytics tooling (e.g. dbt is a must, Stitch/Fivetran, Snowflake/BigQuery/Redshift, Airflow, Dagster, Looker/Mode/Sigma). Bring a system-oriented and software engineering mindset to the Analytics Engineering practice. We’re looking to build frameworks that manage data, and minimize bespoke queries. Deep knowledge of crafting dimensional and fact models in modern data fashion. Have a passion for enabling the developer experience of data, and being obsessed with giving

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 We're hiring a Marketing Analytics Manager to establish how Marketing at Baseten makes decisions with data. Marketing at Baseten is scaling fast: more spend, more campaigns, more model launches and more inbound. This is a foundational, hands-on role and the first dedicated Marketing Analytics hire. You'll work directly with Demand Gen, Field Marketing, MOps and Product Marketing alongside GTM, Finance, Product and Engineering to stitch together activities and outcomes across the funnel. You'll build the data models that connect acquisition, engagement, activation, product usage and revenue. You’ll design dashboards, tools, semantic layers and plugins that enable teams to answer questions. Along the way, you’ll develop an understanding of how customers use Baseten and with this, define how our systems and product can improve. RESPONSIBILITIES Define how Marketing success is measured: establish metrics across audience growth, acquisition, activation, engagement, usage, pipeline and revenue. Build the marketing data foundation: ingest and model data across Salesforce, HubSpot, Google Analytics, advertising platforms, web, email, product and third-party sources. Create a medallion architecture that connects the prospect and customer journeys across systems, from first touch through signup, onboarding, activation and expansion. Understand our audiences: develop audience and segmentation frameworks based on customer a

About the Team The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. About the role: We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI! In this role, you will: Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse. Develop canonical datasets to track key product metrics including user growth, engagement, and revenue. Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions. Implement ro

About the Team The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. About the Role We are hiring a Staff-level Data Scientist to help lead the evolution of OpenAI’s core experimentation platform. This role is focused on improving the statistical rigor, reliability, and practical usability of experimentation across the company. You’ll work on some of the hardest problems in online experimentation: sample ratio mismatch detection, variance reduction, bias mitigation, metric design, triggered analysis, heterogeneous treatment effects, sequential testing, and experimentation in complex ML systems. You’ll also help translate advanced statistical concepts into pragmatic systems and product experiences that teams can actually use. This is a highly technical individual contributor role with significant influence across methodology, platform architecture, and experimentation best practices. The ideal candidate combines deep statistical expertise with strong systems intuition and hands-on experience building or operating experimentation platforms at scale. In this role, you will: Drive the statistical direction and technical strategy for OpenAI’s experimentation platform Design and improve experimentation methodolo

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. Learn more about OpenAI’s approach to safety About the Role As an Analytics Engineer in Safety Systems, you will play a pivotal role in building a data-centric culture, enhancing decision-making processes, and driving strategic initiatives through analytics. You will partner closely with Engineering, Research, and Data Science to develop and maintain canonical data sources and source-of-truth dashboards that enable both people and AI agents across the organization to derive trustworthy, actionable insights. You will own the consumption layer for safety metrics: defining intuitive, reliable ways for stakeholders across Safety Systems, partner teams, and leadership to understand the safety of our products, answer safety-related questions independently, and inform product decisions and company strategy. Most importantly, you will be a core member of the Safety Systems team, collaborating with researchers and engineers to advance our goals of safe, robust, and reliable AI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and maintain canonical datasets that serve as sources of truth for safety metrics. Develop and refine data products such as dashboards, reports, agent-enabled workflows, and machine-readable interfaces that empower stakeholders to extract and analyze data independently. Work closely with stakeholders in Engineering, Research, and Data Science to understand their decision-making n

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: The Total Rewards Compensation team serves as a strategic advisor to business leaders, managers, and employees across Airbnb. We are compensation experts with a deep understanding of our stakeholders, problem solvers who use data and insights to drive value, and partners who build the tools, models, and frameworks that support sound compensation decision-making across the company. This role sits within the Compensation function and will work closely with the Technology organization and cross-functional partners including Talent Directors, Recruiting, People Analytics, Finance, and Legal. The Difference You Will Make: We are looking for a Senior Compensation Partner to own Airbnb's compensation strategy for the Technology organization, covering functions such as Engineering, Infrastructure, ML/AI and Data Science. You will be the primary Total Rewards advisor to Technology leadership and the compensation point of contact for Talent Directors and Recruiting, defining how Airbnb competes for AI, ML, and frontier engineering talent. Working alongside our regional Total Rewards Partners, you will hold a global view of how we pay technical talent across all markets. Beyond your client group, you will contribute to the design and strategy of complex global programs, lead core Total Rewards priorities, and build the models and tools the broader Compensation team relies on. You are equally credible advising our most senior technical leaders and in the data behind the recommendation. A Typical Day: Serve as the senior compensation advisor to Technology leadership across func

MongoDB has a great opportunity for a Senior HR Business Partner for our Technical Services organization. HRBPs at MongoDB are responsible for helping business unit leaders and their leadership teams develop and implement a people and culture strategy that best supports their business needs. They act as coaches, trusted advisors, change agents, consultants and thought partners on all things talent within the business. They work closely with other teams within the People Team to perform their role and responsibilities – this includes Employee Experience, Compensation, Culture & Talent Development, Talent Acquisition, HR Operations and People Analytics. This Senior HRBP role is an opportunity for a strategic, commercially minded people leader to shape the talent and organizational agenda for a complex business. The role will partner closely with senior leaders to anticipate people needs, lead through change, translate data into clear recommendations, and build scalable solutions that enable the business to grow. Alongside this strategic partnership, the Senior HRBP will lead critical talent moments, including performance, engagement, succession, and compensation cycles, ensuring they drive meaningful business and people outcomes. We’re open to candidates across North America’s Eastern and Central Time Zones and are flexible on location for the right candidate. Key Responsibilities Builds relationships with leaders to offer thought leadership on organizational and people-related strategy and execution Adopts the culture of the organization and embodies our values and leadership principles Develops a commercial understanding of the business to appropriately guide and influence leaders on their talent agenda Applies expertise in the following areas: organizational design, workforce planning, change management, performance management, career planning, coaching, analysis of people data, compensation (cash and equity), complex employee relations issues, learning and dev

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 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 to ship AI products. THE ROLE We’re hiring a Data Engineer to build and scale Baseten’s internal data platform. This role sits at the intersection of data engineering, analytics, and data science, transforming raw product and business data into reliable datasets that power decision-making. You’ll design the data models, pipelines, and analytics infrastructure that enable teams across Product, Engineering, Finance, Marketing, and Sales to understand usage and performance. This includes working with AI inference, infrastructure, and observability data to generate insights about the product, business operations and platform economics. You’ll partner closely with stakeholders to build robust, scalable pipelines, define company-wide metrics that inform strategy and planning. RESPONSIBILITIES Design and maintain core data models and semantic layers Develop and orchestrate batch and streaming data pipelines using technologies such as Apache Beam, Kafka, Airflow, or similar frameworks Analyze inference and infrastructure telemetry , including data from OpenTelemetry, Grafana, and other observability tools Define and maintain company-wide metrics across product usage, performance, and customer lifecycle Enable self-service analytics through agents and tools, with well-structured semantic layers and context Ensure data reliability and quality through testing, documentation, and governance PREFERRED QUALIFICATIONS Understanding of inference metrics s

The Internal Product Analytics (IPA) team is the analytics backbone of Datadog's Product organization. With over thirty products on a single platform, IPA gives PMs and leadership the data, tooling, platform, and analysis they need to make good decisions. The team owns the recurring analytical work the Product org runs on and builds the AI-first workflows that make that analysis faster and more consistent across the org. As Manager of the Internal Product Analytics team, you will directly manage a team of data analysts, partner closely with the PMs your team serves, and partner with the associated platform engineering teams. You will set the direction for how the team delivers analysis, builds AI-first tooling, and partners across functions. This is a role for someone who works well across teams, turning complex data and open questions into clear, trusted answers that PMs and leadership can act on. What You'll Do: Guide and grow the Internal Product Analytics team. Manage, coach, and develop a team of data analysts. Set priorities, hold a high bar for quality, and make sure the team's output is trusted across the Product org. Partner directly with the PM org. Work side by side with the PMs your team serves to frame the questions that matter, shape the analysis, and make sure the answers reach them in a form they can act on. Own the recurring analytics the PM org runs on. Business reviews, feature request analysis, usage and adoption tracking, and pricing analysis. Make this work consistent, repeatable, and fast so PMs get answers when they need them. Build AI-first analytics. Design and ship AI-powered workflows and agents that do the heavy lifting of analysis, from data querying to synthesis to reporting. Set the standard for how the team uses AI so analysis scales without simply adding headcount. Partner across functions. Work with Finance, Data Platform, Engineering, and Revenue teams to align on definitions, source the right data, and turn raw signals into decis

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: The Total Rewards Compensation team serves as a strategic advisor to business leaders, managers, and employees across Airbnb. We are compensation experts with a deep understanding of our stakeholders, problem solvers who use data and insights to drive value, and partners who build the tools, models, and frameworks that support sound compensation decision-making across the company. This role sits within the Compensation function and will work closely with the Technology organization and cross-functional partners including Recruiting, People Analytics, Finance, Legal and Talent. The Difference You Will Make: We are looking for a Technical Compensation Partner to serve as the dedicated compensation partner for the Technology organization, covering Engineering, Infrastructure, Machine Learning, and Data Science. This role will support VP and Director level tech leaders and their Talent Partners as the primary day-to-day compensation resource. The ideal candidate will be a strong business partner and a builder of compensation programs, tools, and data infrastructure, and must be comfortable operating with autonomy in a fast-moving environment. A Typical Day: Serve as the dedicated compensation partner for the Technology organization, supporting VP and Director level leaders, Talent Directors, and People Partners across Engineering, Infrastructure, ML/AI, and Data Science. Act as the primary point of contact for Talent Directors and senior tech leaders on new hire offers, internal equity reviews, leveling decisions, and out-of-cycle requests. Own compensation cycle execution f

About the Team OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner with Product, Engineering, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide. About the Role As a Data Scientist on FinEng, you’ll own the analytics and experimentation that improve our checkout and payments , subscriptions , and pricing & monetization systems. You’ll define the metrics that matter, build the source-of-truth data assets, and design experiments that increase conversion, reduce churn and payment failures, and expand global payment method coverage. Your work will directly influence revenue, customer experience, and how we scale internationally. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Own checkout & payments analytics and experimentation across methods and locales (e.g., bank transfers, emerging rails), improving conversion while monitoring risk and latency. Build and run the experimentation program for in-house checkout—define success metrics and guardrails, execute staged rollouts, and use offline incrementality when online tests aren’t feasible. Create operational visibility and source-of-truth data with FinEng Data Engineering—land team-level metrics, SLAs, and self-serve dashboards that drive proactive action. Lead subscription, retention, and monetization analytics—ship launch-readiness for new subscription features, reduce involuntary churn (e.g., targeted retrials/nudges), and develop elasticity/FX frameworks toward pricing optimality. You might thrive in this role if you have 5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments Fluency in SQL and Python ,

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