Data Scientist, Experimental Projects

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 Experimental Projects team quickly tests new product opportunities for Stripe. We work on brand-new, zero-to-one problems by building prototypes, talking with users, analyzing what we learn, and iterating rapidly.

The team operates across a broad range of problem spaces. Rather than optimizing a single mature product area, you’ll help determine whether new ideas can solve meaningful user problems and become valuable products for Stripe. We’re looking for a Data Scientist who enjoys building, has a strong bias for action, and is comfortable moving from an ambiguous question to a practical test.

Responsibilities

• Use data to identify, evaluate, and shape new product opportunities.
• Partner with engineers and product managers to build and test early product concepts.
• Develop analyses, models, experiments, and prototypes that help the team learn quickly.
• Talk with users and combine qualitative insights with quantitative evidence.
• Define success measures for new ideas and assess whether early results support further investment.
• Work across several new problem areas, adapting your approach as priorities and evidence change.
• Communicate findings clearly, including uncertainty, tradeoffs, and recommended next steps.
• Help establish analytical foundations for projects that may grow into larger product areas.

What you'll do

You’ll partner closely with product managers, engineers, designers, and other cross-functional partners to explore new product opportunities. You’ll use data science throughout the discovery and development process, from identifying promising problems and shaping hypotheses to building early solutions and evaluating results.

Your work may include product analytics, experimentation, statistical modeling, machine learning, causal inference, and rapid prototyping. The specific methods will depend on the opportunity. Success in this role requires choosing the right level of analytical rigor for each stage, working quickly when evidence is limited, and turning what you learn into clear recommendations about what the team should build or test next.

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.

Location Requirement

• San Francisco CA, Seattle WA or New York, NY preferred (50% in office - hybrid)

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.
• Ability to effectively work both independently and with cross-disciplinary teams, including engineering and finance, to deliver impactful results.
• A demonstrated ability to manage and deliver on multiple projects with a high attention to detail.
• Solid business acumen and experience in synthesizing complex analyses into actionable recommendations.
• A track record of building relationships with and influencing the decisions of senior technical leadership.
• A builder's mindset with a willingness to question assumptions and conventional wisdom.
• Proficiency with artificial intelligence 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 using causal inference methods
• A builder’s mindset and willingness to question assumptions and conventional wisdom
• Experience working on ambiguous, zero-to-one problems and turning early evidence into practical decisions
• A strong bias for action, including the ability to identify the fastest credible way to test a hypothesis
• Comfort moving across different problem spaces and learning unfamiliar domains quickly
• Experience with distributed tools such as Spark or Hadoop
• A PhD or MS in a quantitative field, such as statistics, engineering, mathematics, economics, quantitative finance, science, or operations research

Hybrid work at Stripe

This role is available either in an office or a remote location (35+ miles or 56+ km from a Stripe office).

In-office expectations

Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.

Working remotely at Stripe

A remote location is defined as being 35 miles (56 kilometers) or more from one of our offices. While you would be welcome to come into the office for team/business meetings, on-sites, meet-ups, and events, our expectation is you would regularly work from home rather than a Stripe office. Stripe does not cover the cost of relocating to a remote location. We encourage you to apply for roles that match the location where you currently live or plan to live.

Pay and benefits

The annual US base salary range for this role is $159,000 - $288,000. 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 location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process.

Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.

We look forward to hearing from you.

At Stripe, we're looking for people with passion, grit, and integrity. You're encouraged to apply even if your experience doesn't precisely match the job description. Your skills and passion will stand out—and set you apart—especially if your career has taken some extraordinary twists and turns. At Stripe, we welcome diverse perspectives and people who think rigorously and aren't afraid to challenge assumptions. Join us.

Apply now

Please find our California applicant personal information notice here.

The application window will remain open for 100 days after the Job Post is published. However, this opportunity will remain open based on the needs of the business, which may cause the application window to close before or after the 100-day mark.