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
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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 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
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 Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you’ll do We’re looking for a Data Scientist to partner with our Global Growth teams. You’ll play a key role in designing and shipping experiments, as well as identifying improvement opportunities across stripe.com and the dashboard to help businesses worldwide get started on Stripe. You’ll help us understand, grow, and optimize the self-serve user funnel to ensure a consistently high-quality onboarding experience for users globally. As Data Scientists at Stripe, our mission is to ensure that company strate
About the Team OpenAI’s Agentic Data Science team helps shape how AI agents are built, deployed, and improved across our products. We partner with product, engineering, research, and security teams to define meaningful measures of success, understand how our systems behave in the real world, and translate evidence into better decisions. As AI agents become more capable, they can write and execute code, access sensitive systems, and complete increasingly complex tasks with greater autonomy. These capabilities create powerful opportunities to improve cybersecurity, but they also introduce risks that traditional security tools and processes were not designed to address. Meeting this moment requires new ways to measure security, evaluate defenses, and distinguish genuine risk reduction from friction that slows users down. About the Role We are looking for a senior data scientist to help define what effective cybersecurity looks like in the age of AI agents. You will work across OpenAI’s Security organization and cybersecurity product teams to measure emerging risks, improve internal security controls, and shape AI-powered security products. The problems are foundational: How do we know whether an agent’s security controls are effective? Which safeguards meaningfully reduce risk, and which create unnecessary friction? When an AI system identifies a potential vulnerability, how do we determine whether the finding is accurate, actionable, and ultimately resolved? How do we detect anomalous behavior or risky access when the systems themselves are changing rapidly? You will report into Data Science while partnering closely with Security, Cyber Product, Engineering, and Research. This is a high-ownership role for someone who can establish a new analytical discipline, operate across organizational boundaries, and turn ambiguous security challenges into measurable improvements. In This Role You Will Define how we measure AI-agent security. Establish metrics and evaluation frame
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 Data Science and Analytics organization at Stripe partners with teams across the company to drive rigorous, data-informed decision-making at scale. Within this org, the Verifications and Greater China data teams deliver critical analytical and data science work—from identity verification and risk modeling to market-specific growth insights—that directly shapes Stripe's ability to serve users safely and expand into new markets. Today, the team comprises individual contributors distributed across Singapore and India, supporting two high-impact pillars. We're looking for a founding Data Science Manager based in Bengaluru to build and lead this growing regional footprint from the ground up. What you'll do This is a rare 0 → 1 leadership role with a dual mandate. Pillar 1—Direct Team Leadership • Manage a team of Data Scientists and Data Analysts (currently 4 individual contributors across India and Singapore) spanning the Verifications and Greater China workstreams. • Own roadmap prioritization, execution quality, and stakeholder alignment for both workstreams. • Drive hiring for open and future roles in India, building a high-caliber data team in a competitive talent market. • Foster individual contributor growth through real-time coaching, mentorship, career development, and performance management. Pillar 2—Regional Data Craft Lead (India Office) • Serve as the founding data craft leader for Stripe's India office. Set quality standards, es
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 Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together. You'll work with some of the most fundamental data at Stripe, and use that data to help drive company-wide initiatives. We have a variety of Data Analytics roles and teams across Stripe and Data Analysts are hired in line with the business needs and domain of the organization they will support. What you’ll do In this role, you'll partner deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. You'll design, build, and own the scalable data infrastructure that powers analytics and reporting across the company. Day to day, you'll translate complex business requirements into reliable data models, own end-to-end pipeline development from raw data ingestion to clean, consumption-ready datasets, and work with leaders to prioritize the highest-impact data investments. You'll go beyond building dashboards—you'll architect the data layer that makes self-service analytics possible and deliver actionable business recommendations through rigorous analysis and data storytelling. Responsibilities Design, build, and maintain scalable data pipelines and ETL/ELT workflows that power production-grade financial reporting, risk measurement, and operational decisioning for Treasury Finance Leverage AI tools (code assistants, L
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 Finance and Strategy Data Science builds the forecasting models, data infrastructure, and analytics tools at the core of how Stripe measures and plans its business. The team owns everything from hierarchical time series and agentic forecasting tools that predict payment volumes and revenue margins, to the governed metrics platform that feeds company-wide dashboards and executive reporting. We partner closely with Finance and Strategy, GTM, and Product stakeholders to directly inform financial decisions across Stripe's entire business. The team combines technical depth, strategic thinking, and executive partnership that develops both technical and business expertise. What you’ll do Data Science Managers at Stripe are responsible for the success of their team. You'll be deeply involved in the modeling and design processes as well as coaching, mentoring, and leading the team. You'll have a deep understanding of how to drive efficient data science teams and you'll have a strong user-focus. You'll be working with data scientists, analysts, and engineers on creating technical solutions and communicating effectively across teams and senior leadership. Responsibilities Drive the roadmap and priorities for your team, and work with many Stripe leaders across the company to enhance our ability to be data-driven. Collaborate with stakeholders across the organization such as engineering, analytics, operations, finance, and marketing. Lead and manage proc
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 Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. The Link Data Science team at Stripe is the dedicated data science and analytics partner for Link - currently with a strong product market fit in offering one-click checkout to shoppers who shop across Stripe’s merchant network, trusted by more than 300M users. The Link team has an exciting roadmap to launch consumer-friendly features to make Link the best way to spend, while continuously generating conversion uplift to our merchants. We are hiring for two data scientists dedicated to: Local Payment Methods - We want to enable consumers across the globe to be able to pay using their preferred local payment method like UPI, PIX etc. This allows me
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 You’ll be joining the data science team at Stripe responsible for our overall infrastructure, with a focus on core systems and cloud platforms. Projects include, but are not limited to: Developing models to predict resource needs as Stripe demand increases; Working closely with engineers to improve the cost and performance of platforms and services; Employing quantitative methods to drive and automate fleet decisions. You will act as a key strategic data partner to the Core Infrastructure organization at Stripe, and help craft, guide, and drive the strategy and tactics needed to help ensure Stripe can continue to scale with efficiency and dependability as our business rapidly grows. What you'll do As a Data Scientist, your role will involve: Analyzing infrastructure usage, efficiency, and workloads to predict demand and inform capacity planning. Developing models and strategies for efficient compute resource consumption and provisioning. Collaborating with engineers, engineering leadership, and finance teams to ensure Stripe makes the right, data-driven, infrastructure decisions. Providing actionable insights and recommendations to improve infrastructure operations to reduce costs and improve reliability. Utilizing your analytical expertise to influence both technical and financial strategies within Stripe. Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements,
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 Payments organization owns some of Stripe's most critical payment flows and a platform that processes hundreds of billions of dollars in payments a year. Our team is responsible for translating complex partner specifications related to network costs (interchange and scheme fees) into simplified logic for internal and external consumption. This also drives decisions and product recommendations to manage the underlying network costs paid by Stripe and our users. The team partners closely with the engineering, product, finance, and partnership groups to manage and understand Stripe's network costs. Our work is core to Stripe's business, as Technical Operations roles in Payments are a dynamic and key component of Stripe's success. We sit at the intersection of product and platform engineers and financial partners, connecting them to ensure that everyone thrives and nothing is lost in translation. What you'll do We're looking to add payment enthusiasts who enjoy interpreting complex cost structures and ever-changing payment network systems to optimize on behalf of Stripe and our users. You'll be instrumental in building Stripe's approach to managing our global network cost base. Responsibilities • Collaborate across the company, including engineering, accounting, financial partnerships, and product teams, to analyze billions of dollars moving through the Stripe platform • Translate network specifications into implementation instructions to cr
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 As Stripe’s user base and global footprint grow dramatically, we have distinctly unique support problems resulting from both our type of scale and the type of businesses we partner with. The Stripe Delivery Center (SDC) strategy will provide operational leverage and expand Stripe’s portfolio of operational capabilities to support the scaled needs of external users and internal Stripe teams. At Stripe, our Mexico City office is a vibrant hub at the forefront of our mission to reshape the financial landscape for businesses worldwide. Our team prioritizes collaboration, innovation, and excellence. As a member of the Mexico City team, you'll be part of a mission-driven community dedicated to enhancing the global economy and increasing the GDP of the internet. We strive for excellence by creating with craft and beauty, while having fun and celebrating our successes together. We cultivate a culture of collaboration, inclusivity, and support where every team member’s voice matters. Our commitment shines through as we handle over a million support cases each year, empowering our users not just to solve problems but to achieve their goals. What you’ll do As an analyst on the Payments Health Operations team, you will be charged with monitoring and maintaining payments performance for Stripe’s largest users. This will include triaging, investigating, and responding to detected regressions in authentication and cost rates; providing in-depth analysis of
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 Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you’ll do We’re looking for a Data Scientist to partner with our Local Payment Methods (LPM) engineering and product teams. You’ll play a key role in understanding, growing, and optimising our LPM business, leveraging data to make strategic business decisions. As Data Scientists at Stripe, it's our mission to ensure that the company strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical modeling, causal inference, optimization, experime
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 Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our Fraud, Losses, and Financial Crime Data Science team builds the models and data products that protect Stripe and its users from fraud, account takeover, and financial crime. We own the full fraud and loss modeling stack - from account takeover detection and card fraud classification to merchant-level loss estimation, unsupervised anomaly detection, and financial crime risk modeling. We partner with Fraud Engineering, Financial Crimes Engineering, and Risk Operations to bring these systems into production and ensure they have measurable impact on Stripe's financial integrity and user trust. What you'll do We're looking for a Data Scientist to join the Fraud Data Science team. In this role, you'll build and improve the models that power Stripe's fraud detection and loss management systems. You'll work closely with Fraud Engineering and Risk Operations to move models from research to production, and you'll use data to surface insights that shape fraud strategy across the business. Data scientists on this team apply supervised and unsupervised machine learning, statistical mod
At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest open customer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! A core value proposition of Trustpilot is Trust. We work hard to ensure that our platform has genuine content from real people with real experiences. That means eliminating fake reviews and acting on signs of suspicious behavior to protect our platform from fraudulent activity. Our Trust Applied AI team’s mission is to use advanced modeling to safeguard the integrity of online reviews, and we have several cross-functional teams devoted to Trust where Applied AI is integral to achieving our goals. We are looking for a Data Scientist to join our Trust team. You and your team will work to develop, deploy, and maintain innovative models at scale, alongside a cross-functional team of software developers, product managers, ML engineers, and designers. You will have the opportunity to collaborate widely across the business with our Technology and Product teams. You will also work closely with stakeholders in Legal and Platform Integrity. To succeed in this role, you should have proven experience in developing and deploying ML models, ideally using graph data. You need a strong technical foundation and hands-on experience in all stages of data preparation, exploration, and modeling. An adaptable mindset and understanding of the interface between Applied AI and engineering are essential as you will be working in cross-disciplinary teams. Experience with deploying solutions into production is expected, as you will be responsible for implementing end-to-end solutions—from data preprocessing
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