Data Scientist

at Stripe

📍 Seattle, United States

USD 193,200-288,000 per year

SENIOR

✅ Hybrid

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

API Data Analysis @ 6 Data Science @ 6 Payments Python @ 6 R @ 6 SQL @ 6 Statistics @ 6

Details

Stripe, LLC. 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. Stripe’s mission is to increase the GDP of the internet.

Responsibilities

Scope, design, build, and maintain APIs, services, and large-scale systems that reliably and efficiently handle billions of money movement requests.
Design the next generation of Stripe products to meet the high-growth needs of the company and its customers.
Analyze product requirements, user needs, and feedback; translate them into technical specifications; and determine design feasibility while considering cost and time constraints.
Review API launches and library shapes for other teams to ensure backward and forward compatibility, coherent patterns, and extensibility meet quality standards.
Represent the team during technical meetings and understand how its systems interact with the broader company landscape.
Mentor early-career engineers to help them grow into independent engineers.
Establish core engineering tenets and design principles for team projects.

Requirements

A master’s degree or foreign equivalent in Statistics, Data Analytics, Engineering, or a related field, plus 5 years of related work experience in data science or quantitative modeling.
Alternatively, a bachelor’s degree or foreign equivalent in Statistics, Data Analytics, Engineering, or a related field, plus 7 years of related work experience in data science or quantitative modeling, including at least 5 years of post-bachelor’s progressive related work experience.
At least 4 years of experience with each of the following:
- SQL.
- Programming languages including Python or R.
- Developing models, tuning thresholds to drive business outcomes, and deploying models in production.
- Translating complex data analysis into actionable business outcomes.
- Writing or contributing to product strategy, roadmaps, or technical design documents.
At least 3 years of experience designing and analyzing production experiments to drive strategic and technical outcomes.

Compensation and Work Schedule

Salary: $193,232–$288,000 per year.
40 hours per week.
50% telecommuting permitted.
Multiple positions available.

Benefits

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