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Data Scientist

StripeSeattle, WA Posted 1mo ago

Workplace
On-site
Type
Full-time
Level
Not stated
Salary
Not listed
SkillsPythonSQLData & AI

Who we are

About Stripe

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. 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.

What you’ll do

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 our company and customers;
  • Analyze product requirements, user needs and feedback and translate them into technical specifications and determine the feasibility of design, taking into account cost and time constraints;
  • Review API launches and library shapes for other teams to ensure that backwards and forward compatibility, coherent patterns, and extensibility meet our quality standards;
  • Act as the team’s representative during technical meetings and understand how their systems interact with the broader landscape within the company;
  • Mentor early-career engineers to help them grow and spin up into independent engineers; and
  • Construct core engineering tenets and design principles for their team’s projects.

Who you are

Minimum requirements

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. 

In the alternative, the employer will accept 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, of which at least 5 years must be post-bachelor’s progressive related work experience.

Must also have 4 years’ experience in each of the following:

  • SQL;
  • Programming languages including Python or R;
  • Developing models and tuning thresholds to drive business outcomes and deployment of the same model in production;
  • Translating complex data analysis into actionable business outcomes;
  • Writing or contributing to product strategy, roadmap, or technical design documents;

Must have 3 years of experience in:

  • Designing and analyzing production experiments to drive strategic and technical outcomes.

Salary: $193,232 - 288,000/yr

This salary range represents the base salary range for the role and any sales commissions/sales bonuses targets, if applicable, would be in addition to the base salary.

40 hrs/week

50% Telecommuting permitted

Multiple Positions Available. 

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. WA53

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JobsPing insights

Our own analysis of this role, based on every open job we track. Updated daily.

Salary benchmark

Data & AI roles in United States · 76 posted USD salaries

25th: $265kMedian $310k75th: $396k

This listing doesn’t publish a USD salary. Use this range as a starting point when you discuss pay. How to negotiate

How in-demand these skills are

Share of all open roles on JobsPing that ask for each skill

Stripe right now

Open roles
776
Remote
15%
New this week
44

Skills they ask for most: SQL, Python, Java, Ruby.

How to stand out for this role

  • Quantify model or analysis impact in business terms (conversion, cost, accuracy lift), not just metrics like AUC.
  • Show the full pipeline you owned: data sourcing, cleaning, modelling, deployment and monitoring.
  • Have a short notebook or write-up ready that explains a trade-off you made and why.
  • List the specific warehouse and orchestration tools you’ve used (e.g. Snowflake, dbt, Airflow).
Our 20-minute tailoring method

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