S Data Scientist, Payments Stripe via Greenhouse Dublin 7112 data science View role

Nubeero Limited; Dublin; Hybrid; EUR 90,000 - 140,000; Full time

Job summary

Stripe is a financial infrastructure platform for businesses. Our Data Science team partners with product and engineering to build models, run experiments, and deliver insights to grow revenue and reduce risk.

We seek a Data Scientist to collaborate with Local Payment Methods (LPM) teams, using data-driven decision making, machine learning, and causal inference to understand, grow, and optimize the LPM business.

Qualifications

• PhD, MSc or MA with 2 years, or BS/BA with 3 years data science or quantitative modeling experience.
• Proficiency in SQL and a computing language such as Python or R.
• Experience with cross-functional teams to deliver results.
• Ability to communicate results clearly and drive impact.
• Ability to manage multiple projects with high attention to detail.
• Strong business acumen and ability to translate analyses into actionable recommendations.
• Proficiency with AI tools to accelerate model development, analysis, and coding.

Responsibilities

• Partner with Local Payment Methods (LPM) engineering and product teams to understand, grow, and optimise the LPM business.
• Build and deploy machine learning models and statistical analyses to inform strategy and decisions.
• Design, run, and analyse experiments including causal inference to quantify impact.
• Translate complex analyses into actionable recommendations for product, risk, and finance.

Skills

SQL proficiency

Python or R

Cross-functional teamwork

Clear communication of results

Project management

Business acumen

AI tools proficiency

Education

PhD, MSc or MA with 2 years data science/quant modeling

BS/BA with 3 years data science/quant modeling

Tools

Spark

Hadoop

Python

R

SQL

Job description

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. The preferred qualifications are a bonus, not a requirement.

• 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)