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Measurement Lead Jobs

401 active opportunities · Updated for October 2026

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Okta
📍 Washington• Full-time• From $240K/yr
1mo ago

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

pythonsqlaws
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Lyft
📍 Toronto• Full-time• From C$172K/yr
1mo ago

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

machine learningaigo
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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

javasqlaws
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Stripe
📍 New York• Full-time• Remote
1mo ago

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 Stripe's growth marketing team is responsible for driving efficient acquisition and activation of millions of businesses globally from solo founders to scaling startups. Paid media is a critical pillar of our self-serve acquisition strategy. The paid media team manages significant investment across search, social, video and other channels to acquire developers, founders, and operators who will build on Stripe. We partner deeply with growth, data science, analytics, data engineering, creative, finance and other marketers to deliver profitable growth via paid media. What you’ll do As Head of Self-Serve Paid Media, you will own and evolve Stripe's self-serve paid acquisition strategy, managing a team of 5-10 paid media experts and working cross-functionally with leaders across analytics, creative, product marketing, growth engineering, and finance. You'll be responsible for a substantial media budget and accountable for delivering efficient, scalable growth in signups, activations, and revenue. In this role, you'll own the long term strategy for how paid media delivers growth in Stripe’s self-serve business. You'll identify new channels and formats, build measurement frameworks that connect spend to business outcomes, and develop your team into world-class practitioners. You'll partner closely with data science to advance our attribution and incrementality capabilities, and with internal and external creative partners to produce high-

REMOTEai
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Stripe
📍 United States• Full-time
1mo ago

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

pythonsqlai
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OpenAI
📍 San Francisco• Full-time
1mo ago

About the team ​​Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security that could scale to an extreme level of severity. Our work involves: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. As we push toward AGI, cybersecurity becomes one of the most important and urgent frontiers: the same systems that can accelerate productivity can also accelerate exploitation. As a Researcher for cybersecurity risks, you will help design and implement an end-to-end mitigation stack to reduce severe cyber misuse across OpenAI’s products. This role requires strong technical depth and close cross-functional collaboration to ensure safeguards are enforceable, scalable, and effective. You’ll contribute directly to building protections that remain robust as products, model capabilities, and attacker behaviors evolve. In this role, you will: Design and implement mitigation components for model-enabled cybersecurity misuse—spanning prevention, monitoring, detection, and enforcement—under the guidance of senior technical and risk leadership. Integrate safeguards across product surfaces in partnership with product and engineering teams, helping ensure protections are consistent, low-latency, and scale with usage and new model capabilities. Evaluate technical trade-offs within the cybersecurity risk domain (coverage, latency, model util

awsrestai
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About the Team The Integrity team builds the systems OpenAI uses to understand, prevent, and respond to misuse across our products. We partner with Product, Policy, Safety Systems, User Operations, Security, Legal, Privacy, OpenAI for Government, and research teams to turn policy and threat models into product controls, review workflows, measurement systems, and enforcement paths. About the Role We are hiring a Senior Engineering Leader for Integrity's engineering efforts for Sensitive Deployments where model capabilities, customer requirements, deployment environments, privacy considerations, and misuse risks raise the operating bar significantly. These include hyperscaler and government deployments and other high-stakes environments, regulated and high-trust enterprise settings, zero data retention and privacy-constrained deployments. The workloads are increasingly agentic where harm can emerge across a sequence of actions rather than a single prompt. The Sensitive Deployments Engineering Manager will focus on high-consequence use cases relevant to government deployments and broader deployment-readiness questions for high-risk domains (e.g., healthcare), while building reusable Integrity capabilities for agentic detection and enforcements in these environments. We're looking for a hands-on engineering leader to guide a team of senior engineers working on OpenAI's most critical deployments. They will lead both the people and technical execution of the team: hiring and developing engineers, setting a high technical bar, and driving ambiguous, high-priority initiatives from early problem definition to durable production outcomes. They will partner closely with Product, Research, Security, Global Affairs, Sales, Solutions, and customer technical teams, while going deep on architecture, infrastructure, and model behavior when needed. In this role, you will: Lead and grow a team of engineers responsible for complex, high-impact deployments of OpenAI technology in sensit

javascripttypescriptpython
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OpenAI
📍 San Francisco• Full-time• $293K – $405K/yr
1mo ago

About the team Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security that could scale to an extreme level of severity. Our work involves: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role As AI agents become more capable at software engineering, and automate more of our internal work, they could become a dangerous cyber threat. People in this role will help OpenAI prepare for security threats from advanced AI agent insiders. In this role, you will: Identify paths by which capable future internal AI agents could compromise OpenAI. Design security controls - focusing on measures with long lead times that benefit from advanced preparation. Stress-test defenses with AI agent evaluations and penetration tests You might thrive in this role if you: Are deeply technical across security and modern infrastructure, and are comfortable digging into the details of operating systems, cloud, containers, CI/CD, or distributed systems. Have strong software engineering skills and enjoy building prototypes yourself. Are interested in engaging with stakeholders and can do so effectively. Bonus: have experience securing cloud infrastructure, and are deeply familiar with core components of the AI stack. Compensation Range: $293K - $405K USD About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy

awsci/cdrest
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DU
DoorDash USA
📍 San Francisco• Full-time• $184.3K – $271K/yr
Just now

About the Team Merchant Analytics helps DoorDash make better product, business, and go-to-market decisions through high-quality analytics, predictive modeling, experimentation, and strategic thought partnership. We work across some of DoorDash’s most important merchant and marketplace priorities, building the measurement, insights, and decision frameworks that improve outcomes for merchants and drive company impact. About the Role We’re hiring two Data Science Managers, each to lead a pod within Merchant Analytics and help shape high-priority product and business decisions. In this role, you will lead a team of data scientists, partner closely with Strategy & Operations, Product, Engineering, and business leaders, and turn ambiguous questions into clear recommendations that influence roadmap and plan outcomes. Success in this role means building a high-performing team, raising the quality and speed of decision-making, and ensuring analytics work is tightly connected to measurable business impact. You will report into Director, Data Science on our Merchant Analytics team in our Analytics organization. You’re excited about this opportunity because you will… Lead and develop a team of data scientists responsible for high-impact analytics, predictive modeling, and decision support tied to DoorDash’s most important product, business, and GTM priorities. Partner closely with Strategy & Operations, Product, Engineering, and business leaders to shape decisions, influence roadmaps, and improve plan-critical metrics. Define success metrics, build measurement frameworks and predictive models, and use experimentation and analysis to connect product and operational levers to business outcomes. Build a high-performing pod that balances analytical rigor, strong prioritization, and clear storytelling in a fast-moving environment. Scale reusable analytics frameworks, tools, models, and best practices that make the broader organization more effective over time. We’re excited

awsgitrest
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DU
DoorDash USA
📍 San Francisco• Full-time• $130.6K – $192K/yr
Just now

About the Team Come help us build and develop tools serving hundreds of engineers internally! We’re looking for a Fullstack Software Engineer to join our Developer Insights team. About the Role Our mission is to improve the developer experience of engineers at DoorDash by building various internal products, including our internal developer portal, Developer Insights. Our success as a platform team depends on the success of the product teams we serve. Because of this, we invest in building a strong community that encourages participation and promotes best practices. You’re excited about this opportunity because you will… Introduce cutting edge technologies to our engineering organization, including tools built on LLMs Build new features for Developer Insights (using Backstage.io) Improve the developer experience for all of our engineers Work and collaborate across team boundaries. Contribute features and bug fixes to upstream open-source projects. Mentor and educate your peers. Lead the team in a technical fashion and assist in roadmap planning and measurement of existing features. Represent the team at large in OKR and engineering all-hands presentations. Context switch from frontend to backend to data depending on the need that arises. We’re excited about you because… You have at least 2 years of experience in web technologies using Typescript with React on the frontend with Java, Kotlin, Python or Go backend experience. You have a product mindset and apply that to how you would build out platform services. You love systems and software, and you're proficient in both. You’re curious and dive deep into different system architectures. You are an organized and excellent written and verbal communicator. You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Compensation The successful candidate’s starti

typescriptpythonjava
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Just now

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

pythonsqlai
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Just now

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

pythonsqlai
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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. Lyft Ads is one of the fastest-growing commerce media businesses in the industry, connecting brands to a high-intent, on-the-move audience across Lyft's rider and driver networks. With proprietary first-party data spanning millions of rides and real-world consumer journeys, Lyft Ads offers advertisers a unique combination of targeting, context, and measurement that traditional platforms cannot replicate. We are building the future of mobility media — and we are looking for exceptional talent to help lead that charge. We are seeking a strategic, highly cross-functional leader to join Lyft Ads as our Sr. Product Marketing Manager for Programmatic Ad Solutions. This is a unique and high-impact role at the intersection of programmatic advertising, revenue partnership development, and go-to-market strategy. You will own three interconnected pillars that are core to Lyft Ads' growth: building our programmatic and Audience Extension business, managing key channel and demand partners, and developing the packaging and pricing strategy that powers our sales organization. This role requires a rare blend of strategic thinking, commercial acumen, and operational execution. You will work closely with Product, Data Science, Sales, and external partners to define how Lyft Ads goes to market — both on-platform and off — and to ensure we are positioned to win against competitors in the rapidly evolving commerce media landscape. Responsibilities: Programmatic Strategy & Audience Extension Go-to-Market Own the end-to-end strategy and go-to-market for Lyft Ads' programmatic business, with a primary focus on Audience Extension solutions that extend Lyft's first-party data and targeting capabilities beyond the app. Develop compelling narratives, positioning frameworks, and packaging structures that clearly articulate L

L
Just now

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. Lyft Ads is one of the fastest-growing commerce media businesses in the industry, connecting brands to a high-intent, on-the-move audience across Lyft's rider and driver networks. With proprietary first-party data spanning millions of rides and real-world consumer journeys, Lyft Ads offers advertisers a unique combination of targeting, context, and measurement that traditional platforms cannot replicate. We are building the future of mobility media — and we are looking for exceptional talent to help lead that charge. We are seeking a strategic, highly cross-functional leader to join Lyft Ads as our Sr. Product Marketing Manager for Programmatic Ad Solutions. This is a unique and high-impact role at the intersection of programmatic advertising, revenue partnership development, and go-to-market strategy. You will own three interconnected pillars that are core to Lyft Ads' growth: building our programmatic and Audience Extension business, managing key channel and demand partners, and developing the packaging and pricing strategy that powers our sales organization. This role requires a rare blend of strategic thinking, commercial acumen, and operational execution. You will work closely with Product, Data Science, Sales, and external partners to define how Lyft Ads goes to market — both on-platform and off — and to ensure we are positioned to win against competitors in the rapidly evolving commerce media landscape. Responsibilities: Programmatic Strategy & Audience Extension Go-to-Market Own the end-to-end strategy and go-to-market for Lyft Ads' programmatic business, with a primary focus on Audience Extension solutions that extend Lyft's first-party data and targeting capabilities beyond the app. Develop compelling narratives, positioning frameworks, and packaging structures that clearly articulate L

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Lyft
📍 San Francisco• Full-time
Just now

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

pythonsqlai
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