Advanced Analytics Lead in United States

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 Guest Engagement AA sits within Marketing Analytics and serves as the analytical backbone for Airbnb's lifecycle marketing programs — the email, push, and in-app communications that reach hundreds of millions of guests across their entire journey. You'll partner closely with Guest Engagement Marketing, MarTech Data Science, and Strategic Finance to drive measurable booking impact through experimentation and insights. The Difference You Will Make You will be the clear analytics owner of Airbnb's guest lifecycle marketing domain — covering abandon journeys, demand generation, onboarding, upsell, and more. This role is expected to drive significant incremental bookings in 2026 by setting the analytics strategy, designing rigorous experiments, and surfacing proactive insights across 30+ active programs. A Typical Day Own the analytics roadmap for Guest Engagement — define what to measure, what to test, and where the biggest opportunities lie across the full guest lifecycle. Specific projects and prioritization decisions should exist because of your recommendations. Design and analyze experiments at scale across abandon journeys, demand gen ML model rollouts, and placement-level A/B tests. Develop measurement frameworks (holdouts, proxy metrics, annualized impact models) to accurately attribute cumulative program impact. Surface proactive insights that go beyond reporting — user segmentation, funnel analysis, fatigue signals, channel optimization — and translate them into strategic recommendations for Director-level marketing leaders. Build scalable, self-serve reporting (

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI infrastructure ecosystem. The Power & Land team owns the energy strategy required to secure reliable, scalable, and economically resilient power for OpenAI’s global data center portfolio. About the Role The Power Trading Lead will own commodity hedging strategy and execution across OpenAI’s data center power portfolio. This role will translate large, dynamic electricity and fuel exposures into practical hedging, procurement, and risk-management strategies that protect infrastructure economics while preserving flexibility for growth. This is an individual contributor lead role and does not have direct reports initially. The role will work across power markets, utility tariffs, retail and wholesale supply structures, natural gas and power hedges, renewable and clean firm products, and portfolio risk analytics to support long-term compute growth. Key Responsibilities Develop and maintain OpenAI’s commodity hedging strategy across electricity, natural gas, and related energy exposures for data center operations and growth. Quantify portfolio exposure by market, site, load shape, tenor, tariff, and supply structure, and translate that exposure into clear hedging recommendations. Evaluate and execute hedging structures including fixed-price supply, forwards, swaps, options, retail supply products, congestion and basis risk mitigation, and related instruments where appropriate. Partner with utilities, suppliers, traders, banks, consultants, and market counterparties to source competitive products and improve risk-adjusted energy economics. Build decision frameworks for when to hedge, how much to hedge, and which risks to retain across different stages of site development, construction, and operations. Coordinate with finance, treasury, legal, procurement, energy regulatory, sustainability, and site-readiness teams to ensure hedging strategy aligns with broa

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary Revenue Integrity is seeking a Lead Director, Informatics (Performance Reporting & Insights) to lead the development and delivery of enterprise risk adjustment analytics and business intelligence solutions. This role transforms complex clinical, operational, and risk adjustment data into actionable insights that will drive provider performance, program efficiency, and executive decision-making. This leader will be responsible for creating action through data storytelling, advanced visualizations, and helping to advance the organization’s reporting strategy through AI and automation. This This role is customer-facing and will provide thought leadership and vision partnership to areas such as Market leads, Finance, Clinical, and Operational partners. The leader must also provide technical guidance to staff on BI tool input modeling and calculations. Key Responsibilities Risk Adjustment Performance Reporting Accountable for timely and accurate sharing of risk adjustment KPIs, trends, and performance drivers at a market, plan, and provider level through dashboards and reporting tools Quantify drivers of risk movement and surface those insights to business leaders for action Assess performance against operational and organizational objectives, including appropriate benchmarking and goal setting <

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron’s Chemistry Lab plays a critical role in advancing semiconductor technology by developing analytical methods that support materials understanding, process development, defect characterization, and next-generation memory innovation. The team applies advanced chemical, optical, and surface characterization techniques to solve complex materials challenges across semiconductor manufacturing and research. We are seeking a highly motivated summer intern to contribute to advanced spectroscopy and nanoscale characterization projects focused on semiconductor thin films, surfaces, interfaces, and process-induced material changes. Working alongside scientists and engineers in Corporate Labs, the intern will develop and apply spectroscopy-based characterization methods, analyze complex materials datasets, and gain experience in experimental design, data analytics, and semiconductor materials research within an industrial laboratory environment. Responsibilities Conduct experiments using advanced spectroscopy and microscopy techniques to characterize semiconductor thin films, surfaces, interfaces, and related materials. Collect, process, analyze, and interpret spectroscopy data, including photoluminescence, fluorescence lifetime, Raman, and AFM-IR datasets, and develop visualization workflows to communicate results. Correlate spectroscopic signatures with material properties, process conditions, surface states, and defect behavior while colla

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior People Analytics Analyst, you'll help GitLab use people data to make clear, informed decisions. The People Technology & Analytics Job Family owns the technology and reporting solutions that support GitLab's People team. Working in partnership with the People Leadership team and cross-functional stakeholders, you'll shape and deliver analytics solutions with a data-first mindset, from scalable reporting and advanced statistical analysis to survey strategy and workflow automation. You don't need extensive GitLab or DevOps knowledge when you join. GitLab's onboarding and training program will

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

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We're looking for a Director of Engineering to join our leadership team in the AI Functions product portfolio, a hybrid director/principal engineer role at the forefront of AI-powered analytics. Our mission is to democratize AI by surfacing powerful AI functions directly in SQL for analyzing structured and unstructured data, with minimal configuration. We handle the full AI lifecycle behind the scenes, so data analysts, engineers, and scientists can build data transformation pipelines with AI using the most sophisticated building blocks seamlessly within their existing SQL workflows. The AI Functions product portfolio represents one of the most strategic and impactful product surfaces within Snowflake, bringing together two of the company's core strengths: its industry-leading ability to process massive volumes of data and its growing capability to make that data AI-ready. By embedding advanced AI and LLM-powered functions directly into SQL, this portfolio transforms Snowflake from a data platform into an intelligent data system where structured and unstructured data can be seamlessly prepared, enriched, and analyzed using AI at scale. This convergence enables customers to operationalize AI within their existing workflows, unlocking faster insights, more powerful applicatio

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 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

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. In partnership with leading cloud providers, hardware manufacturers, utilities, construction partners, and internal engineering organizations, we are delivering hyperscale AI campuses that power the next generation of frontier AI models. Infrastructure Delivery Operations sits at the center of this effort. Our team develops the operating model that connects infrastructure strategy, supply planning, manufacturing operations, and delivery into a single, integrated system that enables OpenAI to deploy AI infrastructure predictably at scale. We partner across Hardware Engineering, Network Engineering, Capacity Delivery, Hardware Operations, Security, Finance, Strategic Sourcing, and external infrastructure partners to create a single, integrated view of program health. Through governance, operational analytics, executive reporting, and scalable operating mechanisms, we enable leaders to proactively manage risk, optimize capacity, and deliver infrastructure predictably at Industrial Compute speed. About the Role We are seeking a Technical Program Manager, Infrastructure Delivery Operations to drive integrated strategy and delivery across OpenAI's rapidly expanding AI infrastructure portfolio. This role sits at the intersection of infrastructure strategy, New Product Introduction (NPI), supply planning, manufacturing operations, and infrastructure delivery. You will lead highly cross-functional programs spanning engineering, supply planning, manufacturing, logistics, construction, commissioning, and operations, ensuring technical and operational dependencies remain synchronized from planning through production readiness. Beyond driving program execution, you will leverage operational insights to improve capacity planning, infrastructure strategy, and deployment readiness. You will also help operationalize new technologies and suppliers by partnering w

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the Team The Finance Data Science team owns the forecasting systems that power Snowflake’s revenue planning and long-term financial strategy. Our work supports corporate planning, executive decision-making, and investor reporting, and we partner closely with Product and Sales to understand customer behavior and product impact. We operate at the intersection of machine learning, statistical research, and corporate finance, building production-grade forecasting infrastructure that is foundational to how the company plans and operates. The Role As a Senior Data Scientist, you will independently lead high-impact modeling initiatives and build production-ready forecasting systems for core financial metrics. You will work on complex, open-ended problems at the intersection of machine learning and business strategy, translating real-world financial questions into rigorous, scalable models. What You’ll Do Design and implement advanced time-series and probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches, multivariate forecasting). Contribute to internal tooling and shared infrastructure that enables scalable forecasting and analytics. Establish best practices for model evaluation, backtesting, uncertainty quantification, and scenario simulat

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a member of our Analytics & Data Insights team, you'll tackle the kind of problems that don't have textbook answers yet, launch products that didn't exist a year ago, and help enterprises understand what foundational AI actually means for their bottom line. As a Data Engineer, you will: Work directly on new customer experiences built on one of the most advanced AI systems in the world Collaborate daily with researchers and engineers who are some of the best in the world at what they do Run implementations end-to-end and see initiatives through to real outcomes Partner across research, marketing, sales, and finance to help define how Cohere grows, with your recommendations feeding directly into products and strategy You may be a good fit if you have: 5+ years of experience working on production-grade data processing systems Strong command of Python and SQL Experience with distributed data processing frameworks such as Apache Beam, Spark, or

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Department Overview The Probe Equipment Engineering team is responsible for ensuring the performance, reliability, and continuous improvement of probe manufacturing equipment within Micron's semiconductor operations. The team partners closely with Manufacturing, Process Integration, Facilities, Quality, and Supplier Engineering organizations to support world-class operational excellence, equipment availability, and product quality while enabling advanced technology node development. Position Overview As a Probe Equipment Engineer at Micron Technology in Boise, Idaho, you will coordinate the installation, modification, upgrade, qualification, and advanced maintenance of manufacturing equipment. You will collaborate with cross-functional teams to increase tool availability, optimize equipment performance, and ensure manufacturing outputs meet or exceed quality standards. In this role, you will leverage data analytics, automation, AI, and machine learning technologies to improve equipment reliability, accelerate problem-solving, and drive manufacturing efficiency. Your work will help enable smarter factory operations and support Micron's continued advancement of AI-driven semiconductor manufacturing capabilities. Responsibilities Drive improvements in equipment availability, relia

ROLE SUMMARY Pfizer Commercial Oncology is introducing the world to the next era of cancer care. With a growing portfolio of novel therapies, industry-leading R&D, and a goal of delivering eight breakthroughs by 2030 across major cancer types, we're translating cutting-edge science into market-shaping impact. Here, you'll partner with exceptional colleagues across scientific, medical, and manufacturing teams, backed by advanced digital and AI-enabled infrastructure and the authority to accelerate medicines from discovery to delivery. Guided by our values of courage, excellence, equity, and joy, you'll have the opportunity to stretch your skills and build a career that evolves with you—across teams, roles, and the Pfizer enterprise. Join us to make history — for patients, for their families, for the future. IBRANCE changed the treatment paradigm for metastatic breast cancer when it launched in 2015. As the brand approaches loss of exclusivity (LOE), this role owns its omnichannel and HCP marketing engine through the LOE timeframe and then carries that same omnichannel discipline forward to stand up NPP and digital execution for the Oncology Business Unit's next wave of breast cancer launches. This is a role for a marketing leader who thrives on solving complex problems in a competitive market and wants both halves of the brand lifecycle; defending an in-line asset through the tape, and building the omnichannel foundation a new set of launches will be built on. This individual must be able to excel in a fast-paced, matrixed environment, make immediate business impact, think outside the box, and actively contribute to a positive team culture. This role will focus on non-personal promotion (NPP), owning IBRANCE's nonpromotional strategy and digital/omnichannel execution (paid search, organic search, paid social, web analytics, search AI, media strategy,

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. The Realtime Defect Analysis (RDA) Yield Technology team supports advanced DRAM research and development by identifying, analyzing, and reducing manufacturing defects that impact yield and product performance. The team partners closely with engineers across R&D and High Volume Manufacturing to improve process stability, accelerate learning cycles, and drive continuous improvement through data-driven decision making. As an RDA Yield Technology Intern, you will gain hands-on experience with innovative semiconductor processing, defect inspection systems, and advanced analytical techniques. You will contribute to projects focused on experimentation, defect detection, data analysis, and process optimization while collaborating with multi-functional engineering teams. This role is ideal for individuals who are passionate about problem solving, root-cause investigation, and leverausingology to improve manufacturing performance. Responsibilities Analyze experimental process flows and defect inspection data to identify anomalies, investigate root causes, and support corrective actions. Partner with R&D and manufacturing teams to improve yield performance through defect detection, process monitoring, and continuous improvement initiatives. Leverage Artificial Intelligence (AI) and data analytics tools to accelerate defect detection, identify yield-impacting trends, automate routine analysis workflows, and generate actionable insights. Use inline defect signals, statistical analys