Data Operations Lead 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

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

Become a part of our caring community Humana Healthy Horizons is looking for a Value-Based Programs Lead who will support successful value-based provider relationships with a focus on improving the provider experience and achieving path-to-value goals. You will lead the beginning-to-end operational support of specialty Medicaid value-based payment (VBP) models in alignment with segment strategy and goals. The Value-Based Programs Lead will be a subject matter expert in VBP and have advanced technical knowledge and experience. Develop new innovative VBP models for range of provider types, such as behavioral health, maternity, specialists, and social determinants of health, creating glide paths to move providers from volume to value. Align scope of work with roadmap for new VBP model development to ensure compliance with Medicaid contractual requirements and RFP commitments. Analyze financial, utilization, and performance data to identify opportunities to drive improvements in quality and/or reductions in total cost of care. Creation of VBP payment strategies and model design, such as developing payment model logic, performance metrics and benchmarks, and financial terms, which align with segment goals. Design and contribute to development of provider reporting packages to help providers understand their overall and detailed performance. Partner with finance team to conduct impact analysis and modeling for new VBP models. Collaborate with team members and matrixed teams to operationalize and rollout of new VBP models. Contribute to developing solutions to operational gaps. Monitor VBP model performance KPIs to identify opportunities to enhance model design based on internal and external feedback and performance data. Ability to translate strategy into models that can be piloted and scaled across markets. <

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI infrastructure ecosystem. The Power Execution team owns the strategy and execution required to secure reliable, scalable, and economically resilient power for OpenAI’s global data center portfolio. The team sits at the intersection of commercial, technical, policy, legal, and operational work, partnering across OpenAI and with utilities, grid operators, regulators, counterparties, and public-sector stakeholders. About the Role The Energy Regulatory Lead will own energy regulatory strategy and execution for OpenAI’s infrastructure growth. This role will be the primary bridge between the Power Execution team and Public Policy and Government Affairs on energy regulatory matters, ensuring that OpenAI’s external engagement is grounded in project realities and that changing policy and regulatory conditions are translated into actionable infrastructure decisions. This is an individual contributor lead role and does not have direct reports initially. The role combines portfolio-level regulatory positioning with transactional regulatory work: evaluating jurisdictional pathways, supporting utility and energy transactions, coordinating approvals and filings, and helping project teams navigate tariffs, interconnection, load-service requirements, market rules, and regulatory risk from diligence through execution. In this role, you will: Develop and maintain OpenAI’s energy regulatory strategy across priority U.S. markets and, as needed, emerging geographies for infrastructure expansion. Coordinate closely with Public Policy and Government Affairs to shape energy regulatory priorities, engagement plans, messaging, and positions before utilities, public utility commissions, grid operators, state energy offices, and other relevant policymakers. Translate project requirements—load size, timing, reliability, cost, carbon, and expansion needs—into clear regulatory objectiv

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role Ramp is known for insane product velocity, sitting at the center of AI and finance, and saving customers meaningful amounts of time and money. Increasingly, companies come to us to understand how the best finance teams are actually operating, whether that’s our own team or the customers we serve. Right now, those conversations happen behind closed doors and Zoom windows. We want to pull them out, write them down, and make them useful to more people. We’re hiring a Finance Storytelling Lead to do exactly that. You will spend roughly half your time embedded with Ramp’s Finance team, learning what it means to run an AI-pilled finance team at a company building AI solutions for finance. The other half of your time will support customer storytelling with the finance customer in mind, working closely with Brand Communications, Sales, and Customer Marketing. For both, you’ll pull out the useful lessons and turn them into stories people want to learn from, whether that means writing in your own voice or for our CFO and Finance leadership team

About the Team The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-To-Market teams to inform high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we’re building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more. We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI’s full potential. About the Role We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability. This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You’ll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI. 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: Build statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains. Own the end-to-end modeling lifecycle , including scoping, feature engineerin

Job Description: Data Scientist, B2B Demand Generation, Growth & Measurement About the Role We are hiring a Data Scientist to lead measurement, experimentation, and decision science for B2B marketing demand generation. You will help us understand which marketing investments create incremental demand, qualified pipeline, and revenue and how to scale them efficiently. Our mandate is to build a rigorous, full-funnel view of how B2B marketing creates demand and moves prospects from awareness and engagement to qualified opportunities, closed-won revenue, and expansion. You will shape how we measure marketing impact and influence across channels, campaigns, audiences, and account segments. In this role, you will partner closely with B2B Marketing, Demand Generation, Growth, Sales, RevOps, Finance to connect marketing activity to qualified pipeline, customer acquisition, and efficient revenue growth. What You’ll Do Define north-star, leading, and guardrail metrics for B2B demand generation, including account engagement, qualified leads and opportunities, sourced and influenced pipeline, conversion rates, pipeline velocity, and incremental ARR. Design and execute measurement and experimentation strategies across channels and campaigns, using randomized tests, audience or geographic holdouts, lift studies, quasi-experimental methods, and other causal approaches suited to long B2B sales cycles. Analyze channel, audience, campaign, creative, content, landing-page, and account-segment performance to identify the drivers of qualified demand, funnel conversion, pipeline quality, and incremental revenue. Partner with Marketing, Sales, RevOps, Finance, Product, and Engineering to improve instrumentation, campaign taxonomy, CRM data quality, lead-to-account matching, and the operating cadence for acting on measurement insights. Build AI-native measurement and decision-support workflows, using LLMs and agents to synthesize campaign performance, surface growth opportunities, and h

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

Operational Account Manager Description - Location Flexible in the US Applies advanced subject matter knowledge to solve complex business issues and is regarded as a subject matter expert. Frequently contributes to the development of new ideas and methods. Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors. Leads and/or provides expertise to functional project teams and may participate in cross-functional initiatives. Acts as an expert providing direction and guidance to process improvements and establishing policies. Frequently represents the organization to external customers/clients. Exercises significant independent judgment within broadly defined policies and practices to determine best method for accomplishing work and achieving objectives. May provide mentoring and guidance to lower level employees. Responsibilities: Manages the operational business relationship of large accounts, often with global/regional reach; serves on account team, providing operational perspectives. Plans and leads business analyses and provides recommendations to sales teams and business units. Acts as a point of escalation and collaborates with other functions to drive resolution of operational issues of high complexity, in support of the customer/partner requirements. Represents the customer/partner needs and provides business requirements to projects of high complexity, and conducts post-project evaluations. Prepares and runs operational performance reviews with the customer/partner and drives improvement plans. Consults and advises on operational matters of high complexity to internal clients up to the Director level. Proactively communicates operational process changes to customers/partners and internal clients; drives the implementa

Become a part of our caring community You have shipped AI products before. You understand the difference between a demo and a production system. You have strong opinions about evaluation frameworks because you have experienced the consequences of operating without them. You are at your best when you own architecture decisions while continuing to build and deliver critical code yourself. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to source documents, and route complex cases to human experts. The output of these systems supports healthcare decisions that impact real members. As a Lead AI Applied Engineer, you will provide technical leadership for AI-enabled products and platforms, define architectural direction, establish engineering standards, and personally design and build the most critical components of our systems. You will lead through both technical expertise and execution, helping the team deliver reliable, scalable, and auditable AI solutions in a highly regulated healthcare environment. Why Join Us Lead the architecture of production AI systems where LLMs are foundational to the product experience. Make key technical decisions regarding model selection, system boundaries, platform architecture, and build-versus-buy strategies. Own the highest-risk and highest-impact technical challenges involving reliability, explainability, and correctness. Influence engineering culture and establish standards that shape how the team builds and ships AI products. Work on systems operating at meaningful scale, processing millions of documents and supporting healthcare decisions across a large member population. Partner

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 We’re hiring a highly influential product analytics leader who can turn ambiguous questions into sharp insight, scalable measurement, and recommendations that directly shape what we build. This person will partner closely with Product, Engineering, Design, and Growth to raise the bar on decision quality and establish a more AI-native analytics operating model. Mission Drive the product insight agenda by helping ClickUp make faster, smarter product decisions through rigorous analysis, strong product judgment, and AI-enabled analytics workflows. What You'll Do Own the product analytics agenda across product usage, activation, feature adoption, retention, and expansion, and translate open-ended business questions into structured analyses and clear recommendations Partner with Product, Engineering, and Design to define success metrics early, improve instrumentation quality, and ensure important product surfaces are measurable from launch Build reusable analysis frameworks, semantic layers, metric definitions, and self-serve resources that help product teams answer routine questions faster and more consistently Apply AI-first methods across the analytics workflow, using large language models, coding agents, and automation for tasks like query drafting, QA, validation, documentation, and first-pass synthesis while keeping human judgment at the center of final recommendations Design and interpret experiments, observational analyses, and trend investigations, including situations where data is incomplete or traditional experimentation is not feasible Surface meaningful patterns in behavioral, subscription, and

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role We’re looking for someone to help lead the future of analytics at Ramp. This person will enable Ramp to get 1% better every day by developing data products and insights. They will partner closely with business stakeholders and product, engineering, and design counterparts to prioritize and execute on work, improve reporting, as well as drive results and process improvements. What You’ll Do Full stack development, building models to consume, transform, and expose data to stakeholders and production systems Drive a culture of experimental design, testing agenda, and best practices Contribute to the culture of Ramp’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way Collaborate with P/E/D/D (product, engineering, data and design) teams to develop product roadmaps and measure success Work closely with data engineering teams to capture, move, store, and transform raw data into highly actionable insights, and partner with business teams to turn those insights into action Wha

Datadog's Finance team collaborates with teams across the organization, providing commercial, operational and analytical support to ensure that Datadog's business continues to scale rapidly and efficiently. The Financial Planning & Analysis (FP&A) team analyzes company financial data (revenue, customers, headcount, expenses, etc.) in order to support the business’ growth and success. As an analyst supporting the team, you will play a key role in delivering insights through the management of essential data infrastructure, including our financial planning tool, Pigment. Your role will be highly cross-functional, leveraging systems and data to unlock analytical capabilities for both FP&A and business leaders. Your role is critical in synthesizing information from across the organization to foster operational alignment and support informed strategic decisions. 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: Own the team’s forecasting and reporting software, Pigment, supporting data-driven insights through the development of dashboards and KPIs, both for standard FP&A reports and ad hoc projects Work cross-functionally with FP&A leaders to improve existing datasets and models Ensure data and system best practices in processes across the organization, including during planning and reporting cycles Represent FP&A in the data & analytics community, collaborating with analytics partners across the organization to democratize data and share insights Work on strategic projects and initiatives for senior management, assessing various business opportunities and proposing solutions Support Datadog’s data-based decision making and continued efficient growth Who You Are: 2+ years of professional experience in FP&A, Data 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 . As the Lead Product Analyst- Lifecycle Marketing, you will serve as the strategic analytics partner for lifecycle and CRM initiatives, helping shape retention strategy through cohort-based insights, experimentation, and cross-functional partnership. You will partner deeply with PMM, Product, and Data Science to measure impact, improve lifecycle programs, and identify the highest-leverage opportunities to drive retention. This role is ideal for someone who combines strong analytical rigor, operational execution, and excellent communication skills. You should be comfortable moving from hands-on analysis to clear recommendations, and from detailed experiment readouts to polished presentations for cross-functional and leadership audiences. What you’ll do Be the analytical thought partner for lifecycle, CRM, and retention strategy. Partn

About the Team The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments as well as other OpenAI products worldwide. We operate across the full funnel - from awareness and acquisition through activation, retention, and expansion - using a combination of global performance marketing, AI-powered workflows, in-product optimization, insights, experimentation, and creative ops engineering. About the Role We are hiring a Lifecycle Lead to build the company-wide owned-channel capability that helps teams reach users with relevant, timely, and trustworthy experiences. This senior, hands-on leader will set the lifecycle strategy, partner with Engineering to build the orchestration and deployment platform, and establish the operating model that allows teams across the company to launch and improve evergreen programs safely at scale. You will sit at the intersection of platform, product, and campaign strategy. You will partner with Engineering, Product, Data Science, and Analytics on the underlying systems, and with Product Marketing Managers and other client teams to design journeys that help new, active, and returning users reach value and build durable habits. In this role, you will: Partner with product to set the company-wide vision, roadmap, and operating model for lifecycle and owned-channel engagement. Partner with Engineering, Product, Data Science, and Analytics to shape the tooling and infrastructure for identity, audiences, eligibility, consent, triggers, orchestration, decisioning, frequency, experimentation, localization, quality assurance, and observability. Define scalable deployment workflows—including self-service and centrally supported paths, intake, templates, approvals, governance, service levels, and incident response—so teams across the company can launch safely and efficiently. Partner with Product Marketing Managers and other client teams to translate audience, product, and business goals into evergreen journey stra