
Stripe · Dublin
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 ...
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.
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.
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.
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.
analytics, causal inference, and experimentation
Operations Research)
This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Data Scientist Adyen is looking for a Senior Data Scientist with deep expertise in statistical hypothesis testing, experimental design, and quantitative research methods to join the Experimentation Platform team in Amsterdam. We want to significantly increase the breadth of Experimentation at Adyen and that requires cutting-edge statistics. You will help to research and implement innovative hypothesis testing approaches that drive experimentation at industry-leading scale. You will also work with a diverse set of users, advocating and mentoring on best practices in experimental design, interpretation of results, and evidence-based decision-making. In this role, you will: * Research and implement industry-leading statistical methods to provide robust statistical signals across multiple business domains and contexts, optimising for time-to-signal and experiment quality; * Develop and apply a deep knowledge of Adyen’s specific domain context in order to prioritise statistical methodologies and approaches that maximise business value; * Stay up-to-date with the latest research and developments in statistical hypothesis testing; * Collaborate closely with your multi-disciplinary team of backend/frontend/data engineers to help scope and define requirements for new platform features, ensuring statistical methods are integrated appropriately; * Collaborate with data scientists across Adyen to identify opportunities for the novel application of statistical and data science techniques to challenging problems; * Work closely with platform users to provide guidance and enable them for success; promoting experiment-driven culture and product development practices. Who You Are: * You have 5+ years of experience as a data scientist, including 2+ years working on an experimentation platform (or similar); * You have a Master’s or Ph.D. in Statistics, Mathematics, Data Science, Computer Science, or a related quantitative field; * You have a strong theoretical understanding of advanced frequentist and Bayesian hypothesis testing (e.g. sequential testing, e-processes, etc) as well as causal inference techniques and a proven track record of implementing such methods at scale; * You have experience designing and analysing controlled experiments in an applied setting to provide tangible business outcomes; * You have experience leveraging a big data framework to create the pipelines needed to gather experiment data; * You have a strong understanding of software engineering practices as well as data engineering principles; * You have strong familiarity with the standard data science toolkit, such as (py)spark, Pandas, SciPy, numpy, and Airflow; * You have an experimental mindset with a launch fast and iterate mentality; * You have proven experience in leading projects from ideation to deployment. You have experience working with a wide range of stakeholders and can clearly communicate complex outcomes over a wide range of audiences. Our Diversity, Equity and Inclusion commitments Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you’re from, we welcome you to be your true self at Adyen. Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application! What’s next? Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility. This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.
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)
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)