7112 Data Science

Stripe

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 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 * Bachelors + 8 years or Masters + 6 years or Phd + 3 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 MSc in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

Stripe

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 special focus on Stripe’s security. Projects include, but are not limited to: * Leverage internal telemetry and logs to understand and design secure and safe access controls to sensitive data; * Develop methods to model, quantify, and ultimately de-risk security-related incidents on Stripe data, assets, and networks; * Collaborate across the company with engineering, PMs, and others to better understand, measure, and ultimately detect various malicious attack vectors.   You will act as a key strategic data partner to the Security organization at Stripe, and help craft, guide, and drive the strategy and tactics needed to help ensure Stripe keeps and maintains the highest level of safety and security for critical business assets and customer data.   What you'll do Responsibilities * Provide senior technical direction to data teams on horizontal technical areas, including detection, modeling, metrics, observability, etc. Assume hands-on leadership, especially when helping teams resolve complex problems through iterative execution. * Identify broad company problems and opportunities that can be tackled through data science * Work with relevant teams to design and build the quantitative outputs and artifacts that deliver outsized value to our users and our business. * Provide data-driven guidance to cross-functional partners on strategy for tracking and protecting Stripe assets from external and internal threats. * Contribute to the overall strategy, roadmap, and vision of your data science team and organization. * Evangelize and inspire best practices across data science. Lead by example to build a culture of craftsmanship and innovation. * Provide mentorship to our data science talent to help them grow technically and professionally.   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 * 10+ years of data science experience or equivalent combined industry and research experience in a quantitative field. * Bachelor’s, Master’s, or Ph.D. in a quantitative field (e.g. Statistics, Mathematics, Economics, Operations Research, Quantitative Marketing, Physical Sciences, Engineering, etc.). * Demonstrated experience of leading organization-wide initiatives spanning multiple teams, or leveraging deep domain expertise to influence tech roadmap planning and execution. * Demonstrated ability to effectively collaborate across multiple teams and stakeholders to drive business outcomes. * Experience creating alignment with stakeholders in ambiguous and complex situations, and leading company-level initiatives. * Demonstrated ability to balance execution and velocity with research, statistical depth, and scalable design. * Proficiency with AI tools to accelerate model development, analysis, and coding. * Experience mentoring and investing in the development of peers.   Preferred qualifications * Strong preference for experience working with security or security-adjacent teams, and familiarity with contemporary security tools and practices. * Experience in the end-to-end development and production implementation of machine learning, statistical, or forecasting frameworks (beyond building model prototypes). * Experience developing and deploying metrics and observability frameworks.

Stripe

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, 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, MSc or MA with 2 years, or BS or BA with 3 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 MSc in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

Stripe

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, establish community rituals (knowledge sharing, peer reviews, office hours), and cultivate a strong local data culture. • Act as the go-to point of contact for data craft standards, tooling, and best practices for co-located analysts, even those outside your direct reporting line. • Partner with managers and leads across the broader Data org to ensure consistency in methodology, tooling, and quality bar. • Support onboarding and integration of new data hires in the Bengaluru office. • Over time, this role has the potential to evolve into a Center of Excellence (COE) model—becoming the single point of data leadership in India across multiple product pillars (e.g., Payments, Growth, Marketing), not just Risk. RESPONSIBILITIES • Build, manage, and develop a high-performing, geographically distributed data team. • Define and drive the data roadmap in close partnership with product, engineering, and business stakeholders—ensuring analytical work is tightly coupled to business outcomes. • Establish and raise the bar on analytical rigor, experimentation frameworks, and data science best practices across the team. • Recruit and retain skilled data talent, crafting a compelling hiring narrative anchored in local leadership and craft excellence. • Champion a culture of technical excellence, intellectual curiosity, and operational discipline. • Collaborate with cross-functional partners and other data leaders globally to align priorities, share learnings, and maintain org-wide consistency. • Communicate insights, recommendations, and team progress clearly to senior leadership. 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 • 10+ years of experience in data science, analytics, or a related quantitative field, with 3+ years in a people management role leading data scientists or analysts • Strong technical foundation in SQL, Python or R, statistical modeling, and experimentation design • Demonstrated ability to translate ambiguous business problems into structured analytical frameworks and actionable insights • Experience managing and developing individual contributor talent across multiple levels, including coaching, career pathing, and performance management • Excellent communication and stakeholder management skills—able to influence without authority across functions and time zones along with proven ability to drive alignment and execution across distributed, cross-functional teams   PREFERRED QUALIFICATIONS • Advanced degree (M.S. or Ph.D.) in a quantitative discipline such as Statistics, Economics, Computer Science, Mathematics, or a related field • Experience working in the payments, fintech, or financial services industry • Prior experience building and scaling data teams in a high-growth environment—particularly standing up 0 → 1 functions or teams • Track record of being a builder who has personally architected the rituals, standards, hiring bar, and craft culture for a data team from the ground up • Familiarity with risk, verifications, or compliance-related data domains • Experience operating across Asia-Pacific markets and navigating the nuances of multi-region team management • Passion for developing others and creating environments where individual contributors do the best work of their careers

Stripe

WHO WE ARE ABOUT STRIPE Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. ABOUT THE TEAM The Risk Data Science team builds the data foundations, models, and measurement frameworks that power Stripe's risk and product decisions — from underwriting and reserves to merchant interventions and enablements. We're at an inflection point: as Stripe increasingly offers risk capabilities as a product to platforms and users, we need a data leader to shape how we build, measure, and evolve our risk data strategy across the  WHAT YOU’LL DO We are looking for an experienced data analyst to drive the data strategy for our risk as a product offering. Define the metrics, data products, and analytical frameworks needed as Stripe brings risk capabilities to platforms and connected accounts at scale. Partner with Product, Engineering, and Risk leadership to ensure data investments align with the product roadmap. You will design metrics, pipelines, and data products that serve as the analytical backbone for risk decisioning. You will own the definition, reliability, and visibility of our most important risk metrics. Establish a canonical set of north star and operational metrics and ensure they are trustworthy, well-documented, and consistently surfaced to the right audiences. Build and maintain the infrastructure that keeps these metrics accurate as our data and product landscape evolves, including clear ownership, alerting on regressions, and scalable pipelines that reduce the cost of keeping insights current. You will also own and evolve Stripe's risk experimentation strategy by defining what we test, how we measure, and how we learn. Ensure we can rigorously evaluate the impact of changes to risk policies, merchant journeys, and risk models across diverse merchant populations. Finally, you will mentor and raise the bar for the Data Analysts on the team. Set technical and strategic standards. Guide junior and senior analysts on how to frame ambiguous problems, structure analyses for maximum impact, and communicate findings to senior stakeholders. 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 * 10+ years in Data Analytics, Data Science, or related roles                                           * Track record of defining and driving data strategy across multiple teams — not just executing on a roadmap, but shaping it                                                                                   * Experience designing experimentation frameworks or measurement strategies for complex, multi-variant systems (e.g., risk policies, pricing, marketplace dynamics)                                              * Deep expertise in SQL; proficiency in Python * Strong ability to translate ambiguous business problems into structured analytical approaches and communicate findings to executive stakeholders                                                            * Experience building and scaling data products (metrics frameworks, pipelines, dashboards) that become operational infrastructure, not one-off analyses                                                         * Demonstrated ability to influence without authority across engineering, product, and business teams * Proficiency with AI tools to accelerate model development, analysis and coding PREFERRED QUALIFICATIONS * Master’s degree in Mathematics, Statistics, Economics, Engineering, or a related technical field * Experience in risk, trust & safety, or related domains and understanding of risk in the Fintech space * Experience building data for platform/product offerings where data is part of the product surface, not just internal analytics                                                                               * Familiarity with causal inference and A/B testing in non-standard environments (e.g., where randomization is constrained by risk considerations)

Stripe

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 processes to help the team do its best work and engage effectively with the rest of Stripe. * Manage a high-performing team of data scientists, supporting them to achieve a high level of technical excellence and advance in their careers. * Recruit and onboard great data scientists, in collaboration with Stripe's recruiting team. * Contribute to broad data science initiatives as a member of Stripe's data science management team. 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 * You have at least 3 years of direct management experience leading data science or ML teams, and 10 years of overall data science experience. * You've demonstrated expertise in designing metrics and guiding business decisions with data. * You have technical expertise to drive clarity with staff and senior scientists about architecture and strategic modeling decisions. * You've managed teams that have built and shipped machine learning systems and data products at scale, and have hands-on experience with challenging problems. * You work very well cross-functionally, and are able to think rigorously and make hard decisions and tradeoffs. * You have clear and persuasive communication skills in writing and in speech. * You thrive on a high level of autonomy and responsibility. * You foster a healthy, inclusive, challenging, and supportive work environment. PREFERRED QUALIFICATIONS * A PhD or MS in a quantitative field (e.g., Statistics, Operations Research, Economics, Computer Science, Engineering) * You're comfortable working with geographically distributed teams. * Expertise in time series forecasting, predictive modeling, or optimization * Expertise in data design and building scalable data architectures

Stripe

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, data scientists, and engineers learn and grow together. You'll work with some of Stripe's most fundamental and exciting data, and use that data to help drive company-wide initiatives. We have a variety of Data Analytics roles and teams across Stripe and will seek to align you to the most relevant team based on your background. 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 work closely with partners to extract insights from the rich and complex data at Stripe. You'll also work with leaders to translate business needs into data problems. You'll build metrics, scalable data pipelines, dashboards, and reports to inform and run the business. You'll deliver actionable business insights  through analyses and data storytelling. RESPONSIBILITIES * Work with Treasury Finance, Finance & Strategy, Risk and Engineering to build out analytics and observability framework for Stripe's financial position * Investigate macro signals and build analytical frameworks that inform financial planning and strategic decisions * Develop targeted observability and performance analytics for both standard and event-driven environments, providing key insights to senior leadership on Stripe’s business position as macro/market conditions shift  * Understand and leverage Stripe's data assets to analyze financial performance and develop scalable data foundations for existing and emerging analytical needs * Work with heterogeneous and unstructured data to develop insights and recommendations * Collaborate with data scientists and engineers to build data pipelines, models, and infrastructure that serve business needs * Support ongoing reporting, stakeholder communications, and information requests across Treasury Finance and Finance & Strategy 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: * Must be located in New York or willing to relocate as this role is hybrid * 3–6 years of experience in Data Research & Analysis, Risk Modeling & Analysis roles, Business Intelligence and Data Engineering, building data pipelines and analyzing large datasets to solve problems * Proficiency in SQL and Python * Strong statistical knowledge and business intuition * Ability to clearly communicate results and drive impact * Experience in analytics in FinTech, banking, investment management, corporate finance, treasury, or financial services  * Expertise in visualization and using data insights to make recommendations and achieve goals * Proven ability to manage and deliver on multiple concurrent projects with strong attention to detail * Comfortable collaborating across functions to identify data analytics problems and execute solutions with technical rigor and data-driven insights * Proficiency with AI tools to accelerate model development, analysis, and coding PREFERRED QUALIFICATIONS: * Master's degree in Mathematics, Statistics, Economics, Engineering, or a related technical field * Prior experience at a growth-stage internet or FinTech company * Prior experience in macro analytics, corporate finance, financial planning, and portfolio management * Familiarity with financial and accounting data, time-series data, macroeconomic analysis or economic indicator development * Experience with distributed data frameworks like Hadoop and Spark to write and debug data pipelines * Good understanding of development processes and best practices like engineering standards, code reviews, and testing