Data Scientist in San Francisco

About the Team The Analytics team is looking for experienced Data Scientists and Senior Data Scientists to guide measurement, strategy, and tactical decision-making across the company across a variety of teams and levels. Data Scientists at DoorDash work to uncover insights and turn them into relevant recommendations, driving decisions for the entire organization. Analytics is integral to all operational areas at DoorDash. Please apply here for all non-managerial levels within the following analytics teams: Consumer & Growth Business Operations Dasher & Logistics Customer Experience & Integrity Merchant, Ads & Sales New Verticals International Data Science About the Role As a Data Scientist at DoorDash, you'll use your quantitative background to mentor other scientists and dive into large datasets to guide decision-making. We solve a multitude of exciting challenges including customer acquisition, fraud and support, marketing, balancing supply and demand, new city launches, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you! You're excited about this opportunity because you will… Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business Build full-cycle analytics experiments, reports, and dashboards using SQL, R, Python, or other scripting and statistical tools Work with and mentor junior analysts on how to use more advanced methods and solve challenges Produce recommendations and use statistical techniques and hypothesis testing to validate your findings Provide insights to help business and product leaders understand marketplace dynamics, user behaviors, and long-term trends Identify and measure levers to help move essential metrics and make recommendations Work backwards from understanding and sizing problems to ideating solutions Report aga

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 is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges—from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. We are looking for an experienced and highly motivated Data Scientist to join the Central Market Management team and lead key initiatives that enhance the quality of our overall decision-making. You’ll work cross functionally with other Data Scientists, Data Analysts, Product Managers, and Finance partners to make sure we are making the most financially efficient decisions to scale our business. You will identify gaps in our operational processes and measurements, and work to create strategies, frameworks, and models to help address them and deliver impact. Responsibilities Leverage data and analytical frameworks to identify opportunities for improving operational efficiency Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope Define and implement a robust attribution framework to evaluate the performance of high-stakes decisions Act as a technical lead, guiding other Data Scientists and fostering a culture of analytical excellence Write efficient, clean, production-level code (Python, SQL), ensuring reproducibility, documentation, and long-term maintainability of analytical assets B

About Us Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X , and discover the projects we’re solving on our Blog . Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Role Join the Monetization team at Twitch, where we build the products that help creators make a living on the platform. You'll work on products like Subscriptions, Bits, and Gifting, and the pricing and packaging decisions behind them. You'll partner closely with product, engineering, finance, and data teams to measure the impact of new features, design and analyze experiments, and apply causal inference methods to inform decisions where A/B testing isn't possible. The work ranges from high-velocity experimentation on consumer-facing products to deeper pricing, policy, and segmentation analyses where causal identification is the central challenge. This role is well-suited for someone with a strong economics or causal ML foundation who wants to apply rigorous statistical thinking to real product decisions at scale. You'll need to be comfortable writing SQL, working with imperfect data, and partnering with stakeholders to turn analysis into product impact. Our team is based at Twitch HQ in San Francisco, CA. You can work in San Francisco, CA; New York, NY; or Seattle, WA You Will: Apply causal inference methods where experimentation isn't feasible Develop models and analyses that inform pricing, segmentation, and revenue optimization Design, run, and analyze A/B experiments Pa

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

About the Team The Analytics team is looking for Data Scientists to guide measurement, strategy, and tactical decision-making using Advanced Analytics approaches, as we expand our platform across the globe. Data Scientists at DoorDash work to uncover insights and turn them into actionable recommendations, helping drive decisions for the entire organisation. Analytics is very integral to all operational areas at DoorDash. About the Role Data Science at DoorDash involves diving deeper into our data to solve crucial business problems, ideate & run experiments to solve for insights gleaned from this deep dive and work with a cross-functional team to drive real-world operational change. This is a rare operational and actionable data-driven experience. We solve many exciting challenges from all three sides of our marketplace including customer acquisition, balancing supply and demand, fraud and support, marketing, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, are excited to build a market from 0 to 1, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you! You're excited about this opportunity because you will… As a senior Individual Contributor, mentor and influence junior Data Scientists in investigating complex issues and uncovering key drivers of our business Influence the Product and Operations roadmap by making actionable recommendations based on data Interface frequently with senior leadership to showcase your team’s work and tackle complex business problems Drive measurement strategy for the area under scope, defining success metrics and implementing best practices around experiment design and statistical analysis Develop a strategic learning roadmap based on data observations, strategic questions, and hypotheses We're excited about you because you have… A degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain 8+ years of experi

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 is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions.We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Lyft Business builds products that help organizations move the people who matter most - employees, customers, patients, and guests - easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We are seeking a Senior Data Scientist to lead technical initiatives across the entire Lyft Business product suite. In this role, you will shape the technical vision, define algorithmic roadmaps, and drive execution for data science projects that accelerate growth, improve operational efficiency, and deliver measurable value to our enterprise partners. You’ll collaborate closely with Product, Engineering, Design, and Go-to-Market teams to build production ML models, experimentation frameworks, and advanced analytics that inform strategy and power product innovation. This is a high-visibility, high-impact role with direct influence on Lyft’s enterprise offerings. The ideal candidate will bring deep expertise in algorithm development, machine learning, causal inference, and experimentation, alongside strong business acumen in B2B contexts and a proven track record of t

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 Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems.&n

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing data structures and data warehouse architecture, this team serves as the foundation for decision-making at DoorDash. The focus extends to enhancing the developer experience by creating tools that support the organization's high-velocity demands. To lead the growing team of Data engineers we are looking for managers who are passionate about Data and are thought leaders in coaching, guiding and leading teams to make Data a winning edge for DoorDash. About the Role DoorDash is looking for a Data Engineering Manager to guide the development of enterprise-scale data solutions. This manager will also act as a technical expert on all things related to data architecture to empower the greater community of data engineers, data scientists, and DoorDash partners. Your focus extends to fostering an engineering culture of excellence, empowering engineers to deliver reliable, flexible solutions at scale. Additionally, you'll play a pivotal role in building and nurturing a top-performing team, driving innovation and success in a dynamic, fast-paced environment. You must be located in San Francisco, CA, Sunnyvale, CA, or Seattle, WA for this hybrid position. You’re excited about this opportunity because you will… You are a people leader. You thrive in hiring, building, growing and nurturing impactful business focused data teams You are a technology leader. You drive the technical and strategic vision for the embedded pods and foundational enablers to meet current and future needs for scale and interoperability You strive for continuous improvement of data architecture and development process You think of quick wins

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. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems. Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes Drive collaboration and coordination with cross-functional teams

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About the Role & Team We’re looking for an Engineering Manager to lead the Data Infrastructure team within Statsig Experiment at Amplitude. You will lead a multidisciplinary team of software engineers, data engineers, and data scientists responsible for the systems that power experimentation at scale. The team owns three critical areas: Data ingestion: Collecting and importing experiment exposures, custom events, OpenTelemetry data, and real user monitoring data across SDKs, streaming systems, cloud storage, and customer data warehouses. Data computation: Building distributed computation systems that transform raw data into accurate, timely experiment results. Stats engine: Developing and productionizing the statistical methods that help customers make trustworthy decisions from their experiments. This is not a traditional data engineering management ro

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 Data Science team works closely with partners from Design, Product and Engineering across Airbnb’s product portfolio. Our work involves 0-to-1 innovation, applying sophisticated modeling techniques to critical Airbnb problems and finding new ways to leverage science for the good of the Airbnb community. Web prototypers work with Data Scientists to identify key questions during the development of these new solutions and build software prototypes that answer them. The work of DS prototyping covers everything from designing the right data visualization to focused explorations that help solve key design questions to broad explorations that help validate ideas. The Difference You Will Make: This role is focussed on partnering with the Data Science team to develop prototypes that show the potential of new data models targeting critical business and user problems. Step change advances in ML/AI have the potential to transform Airbnb, but doing that well requires not just building the right models, but also creating the right experience -- your work will be critical in enabling us to do that. Sophisticated and impactful models are often complex and hard to understand -- by building effective prototypes you can help close that gap and allow innovation to flourish. Your prototypes will enable leadership to make critical and strategic business decisions by demonstrating technical feasibility, suggesting implementation approaches, enabling user studies, and more. A Typical Day: As a web prototyper, you will create prototypes that enable differentiating and industry-leading produc

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

Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems. We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers. What we run on is what we sell. This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you. What You’ll Do Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows Ship quickly through tight experimentation loops while maintaining high quality and reliability Adapt across the stack and learn new tools as needed to solve real problems end-to-end Ideal Experience 3+ years of full-tim