At a Glance
- Tasks: Analyse data and build models to optimise payment methods and drive strategic decisions.
- Company: Join Stripe, a leading financial infrastructure platform transforming the global economy.
- Benefits: Competitive salary, equity options, health benefits, and wellness stipends.
- Other info: Collaborative environment with opportunities for professional growth and innovation.
- Why this job: Make a real impact on how businesses accept payments and grow their revenue.
- Qualifications: Experience in data science, SQL, and programming languages like Python or R.
The predicted salary is between 60000 - 80000 £ per year.
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)
In‑office expectations
Office‑assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico, Bengaluru, India and Dublin, Ireland work 100% from the office. Also, some teams have greater in‑office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in‑person collaboration and learning from each other, while supporting flexibility when possible.
Pay and benefits
The annual salary range for this role in the primary location is €77,200 – €115,800. This range may change if you are hired in another location. For sales roles, the range provided is the role’s On Target Earnings (“OTE”) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and specific location. Applicants interested in this role and who are not located in the primary location may request the annual salary range for their location during the interview process. Specific benefits and details about what compensation is included in the salary range listed above will vary depending on the applicant’s location and can be discussed in more detail during the interview process. Benefits/additional compensation for this role may include: equity, company bonus or sales commissions/bonuses; retirement plans; health benefits; and wellness stipends.
Data Scientist, Payments in London employer: Stripe
Stripe is an exceptional employer that fosters a collaborative and innovative work culture, empowering Data Scientists to leverage their skills in a dynamic environment. With a strong focus on employee growth, Stripe offers numerous opportunities for professional development, competitive compensation, and comprehensive benefits, including equity and wellness stipends. Located in vibrant cities, employees enjoy a balance of in-office collaboration and flexibility, making it an ideal place for those looking to make a meaningful impact in the financial technology sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist, Payments in London
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Stripe.
✨Apply Directly through Our Website
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We think you need these skills to ace Data Scientist, Payments in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Stripe, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Stripe. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Stripe
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Stripe!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.