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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 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 variety of Data Scientists to partner with the Product, Finance, Payments, Security, Risk, Growth, and Go-to-Market teams. You'll work closely with a specific part of the business, playing a crucial role in optimizing our systems and 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, experimentation, and all forms of analytics. Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements PhD with 3 years, MS or MA with 6 years, or BS or BA with 8 years of data science or quantitative modeling experience Proficiency in SQL and a computing language such as Python or R Experience in working with cross-functional teams to deliver results Ability to communicate results clearly and a focus on driving impact A demonstrated ability to manage and deliver on multiple projects with a high attention to detail Strong business acumen and experience in synthesizing complex analyses into actionable recommendations Proficiency with AI tools to accelerate model development, analysis, and coding Preferred qualifications Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation Experience deploying models in production and adjusting model thresholds to improve performance Experience designing, running, and analyzing complex experiments or leveraging causal inference designs A builder's mindset with a willingness to question assumptions and conventional wisdom Experience with distributed tools such as Spark, Hadoop, etc. A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

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 Security Business Enablement (SBE) is Stripe's commercial security function: the interface between Stripe's internal security program and its Go-to-Market organization. We make sure security and compliance requirements never block, delay, or devalue Stripe's deals. This work is about customer trust: businesses entrust Stripe with critical financial infrastructure, and their security teams need confidence that Stripe meets rigorous standards before, during, and after the sale. We make that trust tangible with accurate, consistent evidence of Stripe's security posture. We own security due diligence end to end: questionnaire response, compliance evidence, live security reviews, gap and exception management, contractual security exhibits, rapid response during industry-wide events, and executive briefings. We engage customers directly, up to CISO level, and equip sales teams to handle security conversations on their own. Our scope is unusually broad: one assessment can span security, privacy, business continuity, and resilience, translating deep control detail into language procurement, legal, and a CISO can each act on. We are often the first team asked to represent emerging parts of Stripe's posture. We work at the intersection of security, AI, and Go-to-Market. Our platform is built on authoritative grounding: answers are retrieved from a knowledge base we maintain and validate, not generated from first principles, so they are consistent and source-traceable. Our POC proved the concept and outgrew what agent builders alone can do; taking it to production quality is the engineering problem this role exists to solve. What you’ll do Responsibilities Design, build, and scale an AI-powered platform that delivers validated answers to security questions on demand, for both the sales teams who ask them and the customers who need them, replacing inconsistent ad-hoc responses with consistent, source-traceable ones Build the retrieval, content pipeline orchestration, and integration layers that off-the-shelf tooling cannot deliver, including support for multiple cloud environments and Stripe's full and growing product portfolio, so that answers stay accurate as Stripe's infrastructure and products evolve Build automations that keep security content current as Stripe rapidly adopts new technologies and introduces new controls, including automated refresh and review cycles that route content to subject-matter experts and Legal for validation Build the capability to manage industry-standard certifications and assessment frameworks, including the Shared Assessments SIG and the Cloud Security Alliance CAIQ Build analytics and evaluation capabilities that measure and continuously improve the performance and coverage of the security content library Extend the same platform and knowledge base to power a public and authenticated Trust Center, giving customers direct self-service access to Stripe's security, privacy, resilience, and compliance posture Partner with security analysts and with Security, Privacy, Legal, and Compliance stakeholders to expand coverage across Stripe's full security surface area, and own the reliability and operational health of what you build Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements 2+ years of software engineering experience building production systems Strong coding skills in any programming language (we understand new languages can be learned on the job so our interview process is language agnostic) Comfort working with retrieval-augmented architectures, content pipelines, and AI/LLM integrations, or demonstrated ability to learn quickly in these areas Experience building workflow automation, including scheduled jobs, approval routing, and multi-stakeholder review processes Comfortable instrumenting systems and working with data to measure quality, coverage, and performance, then using those measurements to drive improvement Experience creating projects from scratch, taking ownership, and driving work to completion with minimal supervision Strong communication skills and the ability to collaborate effectively with non-engineering stakeholders (security analysts, sales teams, legal) Seek out opportunities for impact and can execute in a complex, cross-functional environment Preferred qualifications Experience building AI-driven products or workflows, particularly retrieval-augmented generation (RAG) systems or knowledge management platforms Experience building evaluation frameworks for AI systems, such as measuring retrieval quality, answer accuracy, or coverage gaps Familiarity with cloud security concepts across AWS and/or Azure Previous experience with security software engineering, compliance tooling, or GRC platforms Familiarity with security assessment frameworks and standards such as the Shared Assessments SIG, Cloud Security Alliance CAIQ, SOC 2, PCI DSS, or ISO 27001 Experience with content management systems, structured content modeling, or documentation-as-code approaches Experience building customer-facing or internal self-service tools at scale Comfort working in a small team where individual contributions have outsized, visible impact

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 focuses on developing products and platforms that enable users to accept payments from customers efficiently. This includes building APIs for processing payments, enabling regional, non-card payment options, and extending Stripe's capabilities to make it easy for businesses to accept in-person payments. The Risk Engineering organization develops products that minimize financial and regulatory risks while ensuring a seamless user experience, thereby safeguarding Stripe's brand and financial stability. The Premium Merchant Experiences team helps businesses using Stripe succeed by providing high-quality, contextual, and timely premium support options. Our Dublin-based team is a startup within Stripe, building a greenfield product—offering both automated, AI-driven support and improved access to technical experts across Stripe. The Supportability Decisions team is a new, high-ownership team solving some of Stripe’s hardest risk problems. We build technology that helps Stripe distinguish legitimate businesses from bad actors at scale, combining sophisticated engineering, AI-assisted investigation, and meaningful real-world impact. The Payments Intelligence team is dedicated to simplifying and scaling online payments for merchants. Our primary objective is to maximize payment performance by optimizing conversion rates, minimizing costs, and managing fraud, regardless of whether a merchant processes payments via Stripe. We are responsible for developing products such as Radar, Authorization Boost and Authentication, focusing on the creation of high-performance services and seamless user experiences. Team matching—exact team matching for one of the subteams within this org will begin during final stages. Please note we may also consider you for different orgs based on your experience, location, etc. What you'll do We're looking for software engineers who are interested in building software services and platforms that impact thousands of employees and millions of Stripe users, regardless of whether they're an end user, developer, or partner. Responsibilities Work with a wide range of systems, processes, and technologies to own and solve problems from end-to-end Work closely with engineers, designers, and product managers to build new features and products Uphold our high engineering standards and bring consistency to the many codebases and processes you encounter Build elegant APIs and user experiences that enable merchants to run and scale their businesses on top of Stripe Contribute to the design and architecture of the next generation of Stripe's infrastructure, to meet the high-growth needs of our company and customers for years to come Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements 2–12+ years of industry software engineering experience (does not include internships or co-ops) You work effectively across the stack from top to bottom, comfortably navigating codebases with different languages and tools You're equally comfortable shipping user-facing experiences as you are writing custom queries to analyze experiment results Strong coding skills in any programming language (we understand new languages can be learned on the job, so our interview process is language-agnostic) Strong collaboration skills, with the ability to work across workstreams within your team and contribute to your peers' success Ability to thrive on a high level of autonomy and responsibility, and think of yourself as entrepreneurial Interest in working as a generalist across varying technologies and stacks to solve problems and delight both internal and external users Preferred qualifications Experience working in high-growth teams similar to Stripe Experience building financial systems or tools for financial experts

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 Terminal helps Stripe users extend their online presence into the physical world. The Terminal team’s mission is to make it as easy for businesses to accept in-person payments as the Stripe API has done for online payments. With Terminal, businesses can unlock in-person payments use cases that are right for their business model—whether it’s creating a flagship retail experience, extending their website to a pop-up store, or enabling a mobile point-of-sale at their next event. We are looking for: You will be responsible for all aspects of software development, which includes building, writing automated tests, and deploying software on our embedded payments platforms. This team works closely with partner teams throughout the hardware and software product lifecycle, from hardware manufacturing to Android application teams. What you’ll do Design, develop and maintain user interfaces and underlying functionality for embedded point-of-sale software that handle secure payment processing across several products simultaneously. Implement industry standard protocols to match product capabilities. Create, maintain, and execute application unit tests as part of Continuous Integration. Analyze bug reports and manage the defect resolution process (disposition issues, resolve issues, and report issue status). Work closely with QA staff to ensure appropriate test cases are created, maintained, and executed. Collaborate on system-side code, communication protocol design, and kernel development. Interact with global teams with excellent communication skills to provide support information. Routinely perform code reviews to ensure high quality designs and implementation. Assist in ensuring quality and timeliness of product and feature development. Proactively solve problems and work independently and within a team environment, with limited guidance. Work closely with your hardware counterparts on product design and have the ability to read schematics, provide feedback on I/O mapping, developing manufacturing test software to ensure the devices are built to specification. Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements 2+ years software development experience. 2+ years working with embedded, mobile, or other connected devices. Proficiency in embedded programming language C. Experience using automated testing, build systems, or device firmware communication. Experience with embedded systems, knowledge of operating systems, familiarity with software development tools, understanding of hardware-software interfaces. Experience architecting and developing multithreaded applications, preferably in embedded systems. Experience with common communications protocols (e.g., SPI, UART, I2C, USB, and others), debugging practices (e.g., JTAG and associated GDB integrations), and basic electrical design principles. Experience adding, monitoring and parsing telemetry data to proactively resolve issues. Degree in CS, EE, or equivalent practical experience. Fluent in spoken and written English. Preferred qualifications Proficiency in C++ or Golang is highly advantageous. Experience developing on ARM platforms. Experience with point-of-sale hardware and peripherals. Knowledge of EMV standards and payment protocols. Knowledge of PCI standards, transaction processing, and related retail payment technologies. Knowledge of low-level security architectures, including TrustZone, anti-tamper mechanisms, Secure Boot, and Hardware Root of Trust. Knowledge of foundational cryptography, including symmetric/asymmetric algorithms and secure key exchange protocols.

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 variety of Data Scientists to partner with the Product, Finance, Payments, Security, Risk, Growth, and Go-to-Market teams. You'll work closely with a specific part of the business, playing a crucial role in optimizing our systems and 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, experimentation, and all forms of analytics. Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience Proficiency in SQL and a computing language such as Python or R Experience in working with cross-functional teams to deliver results Ability to communicate results clearly and a focus on driving impact A demonstrated ability to manage and deliver on multiple projects with a high attention to detail Strong business acumen and experience in synthesizing complex analyses into actionable recommendations Proficiency with AI tools to accelerate model development, analysis, and coding Preferred qualifications Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation Experience deploying models in production and adjusting model thresholds to improve performance Experience designing, running, and analyzing complex experiments or leveraging causal inference designs A builder's mindset with a willingness to question assumptions and conventional wisdom Experience with distributed tools such as Spark, Hadoop, etc. A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

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 Organization Money as a Service (MaaS) oversees a diverse portfolio of Stripe's core platforms and services. Our Stripe Treasury suite helps users manage and move their funds with ease, providing the robust financial infrastructure and tools they need to power their businesses on a global scale. Team Matching: exact team matching for one of the subteams within this org will begin during final stages. Please note we may also consider you for different orgs based on your experience, location, etc. More information on our team matching process can be found here . What you’ll do We’re looking for Backend Engineers who want to make an impact on managing money at a global scale with a passion for building ergonomic APIs. You’ll play a key role in extending our foundational Money Management APIs and services powering our Treasury products globally. Our team collaborates with many cross-functional teams – from Infrastructure to Product Manager – at Stripe to deliver innovative solutions that address evolving user needs. Responsibilities Scope, design, build, and maintain APIs, services, and large-scale systems that reliably and efficiently handle billions of money movement requests Debug and solve critical production issues across services and multiple levels of the stack Mentor engineers to help them grow Collaborate with stakeholders across the company to build new features at large-scale, while improving internal engineering standards, tooling, and processes Collaborate effectively in a distributed and hybrid team, maintaining open communication and strong connections with colleagues Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements 2-12+ years of industry software engineering experience (does not include internships nor includes co-ops) Strong coding skills in any programming language (we understand new languages can be learned on the job so our interview process is language agnostic) Strong collaboration skills, can work across workstreams within your team and contribute to your peers’ success Have the ability to thrive on a high level of autonomy, responsibility, and think of yourself as entrepreneurial Interest in working as a generalist across varying technologies and stacks to solve problems and delight both internal and external users Preferred Qualifications Experience with large-scale financial tracking systems Good understanding and practical knowledge in cloud based services (e.g. gRPC, GraphQL, Docker/Kubernetes, cloud services such as AWS, etc.)

About the team The Incident Ops team is a global 24/7 team responsible for driving incident response and management from detection to resolution. Stripe is proud of its five 9s reliability and this team is at the forefront of ensuring we keep it that way - working hand-in-hand with Reliability Eng and across the Tech Org. This team of incident response managers (IRM) is defined by our sense of ownership and how we drive incidents to resolution - marshaling the necessary cross-functional resources to respond to and resolve service outages, critical bugs, security attacks and anything that significantly impacts the users of our products. The team is user-first and ensures appropriate external communications from Stripe and senior management to keep our users informed of disruption to their experience of Stripe. The team is skilled in communications, incident handling and technical adeptness as incidents can arise from anywhere and cut across products and orgs in Stripe. What you’ll do As an Incident Response Manager (IRM), you’ll play the key role in driving the right level of response from Stripes to incidents, determining impact, rallying Stripes to mitigate, communicating to users and ensuring appropriate remediations and orchestrate the Root Cause Analysis (RCA) process. You’ll work hand-in-hand with IRMs and engineers globally to ensure solid 24/7 coverage on how we monitor, detect, respond, communicate and mitigate incidents. When not managing incidents, you'll help scale our ability to respond to incidents, improve our operations, analyze data to provide insights and deepen our technical expertise in products. As a result, you’ll be seen as the protector of our users - in minimizing the impact of incidents on their business and ensuring that Stripe is always thinking of our users. Responsibilities Act as an on-call Incident Commander, responsible for driving and managing incident resolution with a high level of urgency, cross-functional collaboration, and accuracy, while partnering with a global and diverse set of teams, including Engineering, Product, Policy, Risks, PR, Legal, Execs, etc. Lead all user-facing incidents across domains at Stripe - including reliability, technical, security, and data privacy "User First" approach to determine impact, providing accurate situation reports, facilitating comms bridges, and ensuring useful and timely external communications to users Proactively update internal stakeholders, make decisions through data and influence by partnering with Engineering, Sales, Support and other cross-functional teams Contribute to the root cause analysis process while conducting post-mortems, remediations identification, and ensure problem management tasks meet SLA and user expectations Drive improvements in the incident handling process and incident management metrics and tooling based on trends and data of Stripe's incidents in collaboration with engineering, product and operations teams Contribute to processes, projects, forums, or groups that impact and grow team culture positively Minimum Requirements 5+ years of demonstrable major incident experience for organizations that run mission critical applications or always-on Saas environments. Demonstrated ability to lead multiple incidents concurrently with authority and influence responders with agency and reasoning skills to resolve ambiguous problems and drive to root cause. Intermediate understanding of application development, application architectures, and applications deployed in cloud environments Good understanding of infrastructure, including physical, virtual, and container-based compute platforms Demonstrated quantitative, and analytical skills in data manipulation using SQL, Splunk or other tools. Excellent task management skills, must be detail-oriented with ability to remain composed, methodical, and think fast in a high-pressured environment. Exceptional written and verbal English communication skills, with the ability to translate complex technical issues for internal and external stakeholders. Preferred qualifications Domain expertise in classes of incidents such as technical, privacy, security or crisis with a strong desire to continuously learn about Stripe's products, technical issues and systems. Ability to review complex technical details regarding ongoing issues/events and convey the key details to senior stakeholders to facilitate real-time decision making. Experience with broad user-facing communications (e.g. status pages, tweets) and/or targeted communications (e.g. direct emails, support ticket responses). Familiarity operating or managing distributed architectures with the ability to correlate system behaviors based on known inter-dependencies. Demonstrated understanding of full stack development and support

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 Growth Platform builds the machine learning systems that help businesses discover and use the Stripe products that meet their needs. Our recommendations reach users across the Dashboard, email, onboarding, documentation, and AI agent interfaces. We combine an understanding of each business with models that decide which recommendation is useful, when to show it, and how to learn from the outcome. Our work spans recommendation and ranking models, contextual bandits, agent-based recommendations, and the data and evaluation systems behind them. We build shared capabilities that product, marketing, and sales teams can use across Stripe. Success means helping businesses take useful actions and adopt products that help them grow, while keeping recommendations relevant and avoiding unnecessary messages. What you’ll do You will build and operate production ML systems that improve how Stripe recommends products, content, and next steps to businesses. You will own work from problem definition and feature development through training, evaluation, deployment, monitoring, and iteration. Working with data scientists, engineers, and product partners, you will turn model improvements into measurable user and business outcomes. Responsibilities Design, train, evaluate, deploy, and maintain models for recommendation, ranking, and personalized action selection across Growth Platform surfaces. Improve contextual bandit and policy-learning approaches, including exploration, reward design, and how recommendations adapt to user context and feedback. Build agent-based recommendation capabilities that use business context to identify relevant products and integration options, with evaluations that test recommendation quality and usefulness. Develop reliable data and feature pipelines for training and inference. Improve data freshness, feature quality, and consistency between training and production. Build reusable tooling for model evaluation, retraining, and safe rollout so the team can test and ship improvements faster. Own the quality and operation of the team's ML components: write tested production code, monitor models and pipelines, investigate failures, and improve reliability, latency, and cost. Design and analyze online experiments with data science partners. Connect offline evaluation to product adoption and incremental impact, with guardrails for dismissals, unsubscribes, and user experience. Partner with product engineering to integrate models into recommendation delivery systems, and with ML infrastructure teams to use and improve Stripe's shared training, feature, and serving capabilities. Work with product, marketing, and sales partners to identify problems that shared ML capabilities can solve, and make practical choices about where modeling adds value. Who you are You are a machine learning engineer with a builder mindset. You care about the business problem, the quality of the model, and what happens after it ships. You can move between modeling and software engineering, make practical tradeoffs, and take ownership of an ambiguous problem through production and measurement. We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements 3+ years of industry experience in machine learning engineering, software engineering, or applied data science, with hands-on experience building and shipping ML models in production. Strong programming skills in Python and experience writing maintainable, tested production code. Practical experience designing, training, and evaluating ML models using frameworks such as PyTorch, TensorFlow, XGBoost, or scikit-learn. Experience building data or feature pipelines, proficiency in SQL, and familiarity with distributed data processing tools such as Spark or PySpark. A strong understanding of statistics, model evaluation, and experimentation, including the ability to recognize data leakage and distinguish offline model improvements from business impact. Experience deploying, monitoring, and debugging production ML systems, and evaluating tradeoffs among model quality, reliability, latency, and cost. Ability to turn an open-ended business problem into a technical approach and collaborate effectively with engineering, data science, product, and business partners. Preferred qualifications Experience with recommendation systems, ranking, personalization, or marketplace and advertising optimization. Experience with contextual bandits, policy learning, causal inference, or off-policy evaluation. Experience building and evaluating LLM applications, including structured extraction, embeddings, or recommendations grounded in user and business context. Experience building reusable ML capabilities used by multiple products or teams, including training automation, feature systems, or model monitoring. Experience with product growth, lifecycle messaging, or systems that balance short-term engagement with longer-term user outcomes.