Measurement Partnerships Lead Jobs

About Supabase Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About the Role We're looking for a Senior Data Analyst, Marketing to join our Data Intelligence team and build the measurement foundation that tells us what's actually working across paid and PLG channels. You'll work closely with Marketing, Growth, and channel owners, helping us move past platform-reported metrics and vanity numbers into causal, trusted answers about what drives pipeline and revenue. This role is ideal for someone who thrives in async, fast-paced environments, is AI-forward in how they work, and is excited about building a measurement function from the ground up. What You'll Be Responsible for Marketing Measurement Strategy Own the end-to-end marketing measurement strategy across experimentation, media mix modeling, and attribution for paid and PLG channels Establish and evolve the attribution framework: how platform data, multi-touch attribution, MMM, and experiments work together to inform decisions Translate complex measurement outputs into clear recommendations on where to invest, what to cut, and how to hit pipeline, revenue, and efficiency targets (CAC, payback, LTV to CAC) Serve as the subject matter expert for marketing measurement, educating stakeholders on causality, model uncertainty, and the limitations of platform-reported metrics Incrementality and Experimentation Design and run always-on incrementality tests, user-level and geo-level, to quantify the causal impact of key channels, campaigns, and tactics Calculate incremental lift, incrementality percent, and incremental ROAS/CPA, and use these to guide budget reallocation Build repeatable analysis templates and playbooks for experiment design, analysis, and readouts so results are consistent across teams Partner

About Supabase Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About this role We’re hiring experienced performance engineers to make performance measurement at Supabase rigorous, repeatable, and actionable by product teams. This role owns the benchmarking and profiling systems we use to detect regressions, explain performance changes, and publish credible numbers for customers and the market. You’ll build the tooling and the methodology and make it easy for product teams to use it correctly. You’d join a new performance team as one of its first members, working alongside a deeply seasoned performance engineer, with the team growing to roughly six this year. There’s no legacy process to inherit — you’ll help define how we measure and communicate performance metrics at Supabase. What you’ll do Build and evolve benchmarking, profiling, and load-testing tooling (cloud, database, and end-to-end). Define benchmark suites and reference workloads that reflect real customer behavior (and evolve them as the products change). Establish performance baselines and regression gates across products (variance tracking, environment control, and detection of changes). Build mechanisms that turn benchmark results into action: triage workflows, owner routing, and clear, reproducible reports. Partner closely with database teams (e.g. Multigres, OrioleDB) to identify bottlenecks and land concrete performance improvements. Enable the company to publish credible, repeatable performance numbers for customers and the market. Help teams self-serve performance testing and make performance a first-class engineering concern. Problems you might work on Build our continuous benchmarking infrastructure so product teams can spot performance regressions early. Ideally, teams can run benchma

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

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role We're redefining how software is built and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. Realizing that vision requires a platform that legitimate users can trust and adversarial actors cannot exploit. We're hiring a Data Scientist to help build Replit's Trust & Safety and Anti-Abuse program from the ground up. You'll turn noisy behavioral, identity, payment, infrastructure, and content signals into the measurement systems, detections, and decisions that protect Replit's users, platform, and economics. You'll work closely with Engineering, Support, Legal, Security, Infrastructure, Money, and Growth to make abuse economically unviable while keeping friction low for legitimate users. Replit sits at the frontier of AI-native abuse. Our platform is a target for phishing and scam hosting, cryptomining, LLM token farming, card and coupon fraud, referral abuse, and increasingly, abuse driven by AI agents themselves. You'll help define how we identify, measure, and respond to these threats without compromising the experience of good users. Who You Are You're a data scientist who moves fast, goes deep, and thinks adversarially. You can spin up an analysis in hours that would take others days, not by cutting corners, but because you've built the intuition and technical toolkit to get to the right answer quickly. You dig past the top-line abuse rate to understand selection effects, missing labels, policy changes, attacker adaptation, and the false positives hidden inside an aggregate metric. You understand that Trust & Safety data is imperfect and outcomes are high stakes. Ground truth is delayed, biased, and often incomple

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. As Sr. Manager, Marketing Analytics, you'll be a senior individual contributor who transforms data into insights and drives decisions and strategy across our marketing channels. You'll own measurement and analytics for campaigns, partners, and field marketing—including attribution modeling, ROI optimization, and emerging AI capabilities—serving as the go-to analytics expert and thought partner for marketing leadership. What You'll Do Drive attribution modeling and full-funnel measurement across all marketing channels Translate data into actionable insights and recommendations for marketing leaders across the business Create forecasts and scenario models to inform annual budget planning and incremental asks Build and maintain self-service dashboards in Tableau for brand, demand gen, digital, and strategic events Partner cross-functionally with Field Analytics, Strategy & Planning, Marketing Leadership, and Data teams on performance narrative and QBRs Partner with the Marketing Data Operations team to maintain data quality across martech systems Implement AI/ML capabilities for predictive modeling and automated insights Design and support marketing experiments with rigorous testing and statistical validation Mentor and provide analytical guidance to junior analysts, and establish best practices for the broader analytics function Stay current with analytics tools and methods to drive competitive advantage What We're Looking For Experience: 8+

Reports to: Head of Developer Growth · New York, NY NOTE: This is not a traditional marketing role, it's a growth role that reports into the Product org. We're hiring someone to build our developer audience the way the best consumer brands build audiences, with a real voice, a point of view, and the speed to act on both. You'll own where and how we show up in the places developers actually spend time, run our developer social channels, expand into new ones, and build the tooling and measurement behind it. This is a builder role, not simply a coordination role. What You'll Do: Own the voice, editorial standard, and publishing cadence for Datadog's developer channels (@datadogdevs on X, Datadog Developers on LinkedIn) Treat replies as a primary surface. The best accounts win in the mentions, not the feed Expand into the places developers actually spend time: Reddit, YouTube, Discord, Bluesky, dev.to, Hacker News, and whatever you make the case for. Always openly as Datadog — developers catch anything else immediately, and you only get caught once Turn shipped engineering work into things people want to read and watch. Releases, changelogs, war stories, the occasional postmortem that deserves a wider audience Build the attribution model connecting what you publish to trials and signups. Nobody is handing you this one Run real experiments: a hypothesis, a readout, and the willingness to kill something publicly when it doesn't work Lead the developer content engine around events Get other people posting — Datadog engineers under their own names, and developers outside the company who already like us and could use the support Track what developers are saying about us and our competitors, and route it back to product and growth Who You Are: You've grown an audience from a small number to a large one You can point to outcomes your content moved, not just reach You're a strong writer with a distinctive voice, and you know the difference between writing about an audience and

Team description At Datadog, AI agents are becoming first-class consumers of observability, security, and software delivery data — from third-party coding agents like Claude Code, Cursor, and Copilot, to our own Bits SRE, Bits Assistant, and Bits Dev Agent. The Agentic Interfaces team owns the platform that connects these agents to Datadog: the MCP Server, the tools and retrieval surfaces agents call into, and — critically — the evaluation systems that tell us whether an agent's experience on Datadog data is actually getting better over time. This role is about that last piece. We're hiring a Staff Applied Scientist to define what "good" means for an Agentic interface at Datadog and to build the measurement systems that make it true. "Good" isn't one number — it spans answer quality, tool-selection accuracy, retrieval relevance, latency, token cost, and end-to-end agent success on real customer workflows. You'll design the evals, build the datasets, define the metrics, and partner with the AI engineers on the team to land the platform that lets every product group at Datadog ship integrations that are demonstrably better release over release. The space is full of open research questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when the tool catalog has hundreds of entries and grows weekly? How do you build a measurement system that catches regressions across first-party and third-party agents at once, without each team writing their own harness? If those are the problems you want to spend your time on, come build this with us. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. What You’ll Do: Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quali

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. As the Senior, Internal Audit AI Enablement & Automation, you will own the day-to-day build, adoption, and measurement of Okta Internal Audit's AI automation program — turning auditor problem statements into working tools, tracking every measurable metric to a verified strategic outcome, and representing Internal Audit across Finance and company-wide AI networks. Okta Internal Audit has moved past the proof-of-concept stage. The AI enablement program is live, tools are in production, and meaningful audit capacity has already been recovered and redeployed into higher-value work — without external development spend. This role exists to scale that engine. The role is the hands-on builder, program coordinator, and adoption driver at the center of that effort. This is not a strategy or advisory role — it is a delivery role. The person in this seat ships tools, closes the loop on problem statements, translates recovered audit capacity into documented strategic value, and represents Internal Audit's automation program in the Finance AI Champions and Company-wide AI Champions networks. What You Will Own Automation Delivery - This is the core of the role. Everything else supports it. Build and maintain AI automations across all Internal Audit functions using the department's existing AI Hub and SOX testing engine as the foundation. Manage the problem statement intake pipeline, acknowledging every submission with a clear disposition (built, deferred, or declined

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. As Director of Marketing Analytics, you'll lead a team that transforms data into insights and drives decisions and strategy across our marketing channels. You'll own measurement and analytics for paid media, digital, partners, and field campaigns—including attribution modeling, ROI optimization, and emerging AI capabilities. What You'll Do Lead and develop a team of analysts; establish best practices and build team capability Own attribution modeling and full-funnel measurement across all marketing channels Take the insights and translate data into actionable insights for marketing leaders across the business. Drive paid and organic digital acquisition strategy through CAC, ROAS, and LTV analysis Build and maintain self-service dashboards in Tableau for demand gen, digital, field, events, and field marketing teams Implement AI/ML capabilities for predictive modeling and automated insights Support marketing experiments with rigorous testing and statistical validation Create forecasts and scenario models to inform annual budget planning Partner cross-functionally with Sales, Marketing Leadership, and Data teams on strategy and QBRs Partner with Marketing Data Operations team to maintain data quality across martech systems Stay current with analytics tools and methods to drive competitive advantage What We're Looking For Experience: 12+ years in Marketing, Analytics, Operations, or BI in B2B SaaS 5+ years managing and developing analytics

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! The AI Product's Data Science org is at the center of the next generation of products at Figma, spanning Make, Figma Agent, Design Systems, and other areas. Data is critical to setting strategy and measurement across these areas. This org engages closely with AI Research and is a driving force behind our evals work and the future of product measurement at scale. With a charge to uplevel Figma’s use of data, the team works alongside other Data Scientists and Engineering to identify ways to implement and democratize new statistical methods, build data frameworks, and incorporate data within Figma’s product development process. This team contributes to the company’s goals by collaborating closely with product managers, engineers, and our finance team to uncover new opportunities, identify inefficiencies and recommend improvements through data-driven insights. As Director, you will lead a team of data scientists and managers, setting the vision for how data shapes strategy across Figma's AI products. You'll work closely with Product, Engineering, Design, and Research leadership to embed data-driven thinking and modern AI-product measurement into how we build. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: Lead, support, and grow a team of data scientists and data science managers with varied strengths and expertise focused on product strategy, internal tooling, and Impact measurement Champion data quality, accessibility, a

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products. As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels. Responsibilities: Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems. Own complex domains and develop long-term roadmaps to maximize business impact. Build statistical pipelines, write production code, and design/analyze experiments. Participate in the science on-call rotation to ensure automated campaigns operate successfully. Experience: Advanced degree in statistics, economics, mathematics, or equivalent industry experience. 4+ years of industry experience in causal inference or data science. Proven ability to apply statistics to unstructured problems and deliver measurable results. Deep technical expertise in causal inference and tackling challenging measurement problems. Expertise in marketing mix modeling is highly preferred. Expertise in SQL and experience with large-scale data platforms. Proficiency in Python and working within production coding environments. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team membe

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products. As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels. Responsibilities: Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems. Own complex domains and develop long-term roadmaps to maximize business impact. Build statistical pipelines, write production code, and design/analyze experiments. Participate in the science on-call rotation to ensure automated campaigns operate successfully. Experience: Advanced degree in statistics, economics, mathematics, or equivalent industry experience. 4+ years of industry experience in causal inference or data science. Proven ability to apply statistics to unstructured problems and deliver measurable results. Deep technical expertise in causal inference and tackling challenging measurement problems. Expertise in marketing mix modeling is highly preferred. Expertise in SQL and experience with large-scale data platforms. Proficiency in Python and working within production coding environments. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team membe

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data Science & Analytics is at the heart of Lyft's products and decision-making. The Rider Experience team sits at the center of how millions of riders discover, choose, and return to Lyft. We are hiring a Data Science Manager to lead our Toronto-based science & analytics team that turns rider behavior into product strategy. This role owns the analytical foundation behind our most consequential rider-facing decisions: how we measure experience quality, where friction costs us retention, and which bets move rider LTV. You will set the measurement and experimentation standards for rider product squads, and translate ambiguous business questions into rigorous, decision-ready analysis that shapes roadmap and investment. You will also lead the team's transition to AI-native data science and analytics workflows, embedding AI tooling into how we explore data, make decisions, and ship products. Responsibilities: Lead and grow a high-performing team of data scientists and analysts with diverse backgrounds Define and drive the data science vision, strategy, and roadmap, aligning with business and product objectives to improve market competitiveness and rider experience Provide strong technical guidance and coaching to the team on complex data science problems Champion data-driven decision-making and prioritization by partnering with product managers, engineers, marketers, and leaders to translate insights into decisions and action Lead deep-dive analyses into large-scale datasets to identify opportunities for improving rider app experience and overall rider product health Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies Mentor and guide the professional and technical development of your team members; help develop the

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Data Quality and Governance owns the infrastructure that makes Stripe's data trustworthy and findable - the Data Catalog, the Knowledge Graph Service, dataset tiering and governance standards, lineage tracking, and the quality scoring system (DQPD) that every engineering team reports against. They're the team that defines what "good data" means at Stripe and then builds the enforcement and measurement tools to drive adoption across the company. What you’ll do Responsibilities Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success Build and operate large-scale data discovery, metadata, or catalog platform Develop strong subject matter expertise and manage the SLAs of data pipelines and full stack web applications that support critical stakeholders Collaborate with product managers and peers across the company to create/improve canonical datasets and data warehouses, use golden paths, and ensure Stripes and customers are using trustworthy data Leverage AI/LLM and Agents at scale to produce and analyze high-quality data on ambiguous problems Have the opportunity to drive the execution of key data initiatives for Stripe, overseeing the entire development lifecycle from planning to delivery while maintaining high standards of quality and timely completion Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuo

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Risk Data Science team builds the data foundations, models, and measurement frameworks that power Stripe's risk and product decisions — from underwriting and reserves to merchant interventions and enablements. We're at an inflection point: as Stripe increasingly offers risk capabilities as a product to platforms and users, we need a data leader to shape how we build, measure, and evolve our risk data strategy across the What you’ll do We are looking for an experienced data analyst to drive the data strategy for our risk as a product offering. Define the metrics, data products, and analytical frameworks needed as Stripe brings risk capabilities to platforms and connected accounts at scale. Partner with Product, Engineering, and Risk leadership to ensure data investments align with the product roadmap. You will design metrics, pipelines, and data products that serve as the analytical backbone for risk decisioning. You will own the definition, reliability, and visibility of our most important risk metrics. Establish a canonical set of north star and operational metrics and ensure they are trustworthy, well-documented, and consistently surfaced to the right audiences. Build and maintain the infrastructure that keeps these metrics accurate as our data and product landscape evolves, including clear ownership, alerting on regressions, and scalable pipelines that reduce the cost of keeping insights current. You will also own and evolve Str