Data Scientist
Confirmed live in the last 24 hours
Stripe

5,001-10,000 employees

Financial infrastructure platform for business payments
Company Overview
Stripe stands out as a leading financial infrastructure platform, providing robust payment solutions that empower businesses of all sizes, from startups to large enterprises, to grow and adapt swiftly. The company's culture encourages technical innovation, offering low-to-no-code solutions and API-based integrations that are easy to implement yet scalable, making it a competitive choice in the industry. With a mission to increase the internet's GDP, Stripe's influence extends globally, with headquarters in both San Francisco and Dublin.
Financial Services
Data & Analytics

Company Stage

Series I

Total Funding

$8.6B

Founded

2010

Headquarters

South San Francisco, California

Growth & Insights
Headcount

6 month growth

5%

1 year growth

7%

2 year growth

29%
Locations
Remote in USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Data Science
R
Apache Spark
SQL
Hadoop
Data Analysis
CategoriesNew
AI & Machine Learning
Data & Analytics
Requirements
  • 2-8+ years of data science/quantitative modeling experience
  • Proficiency in SQL and a computing language such as Python or R
  • Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation
  • 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
  • Solid business acumen and experience in synthesizing complex analyses into actionable recommendations
  • A builder's mindset with a willingness to question assumptions and conventional wisdom
Responsibilities
  • Partner with the Product, Finance, Payments, Risk, Growth and Go-to-Market teams
  • Optimize systems and leverage data to make strategic business decisions
  • Ensure that the company strategy, products, and user interactions make smart use of rich data using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics
Desired Qualifications
  • Experience deploying models in production and adjusting model thresholds to improve performance
  • Experience designing, running, and analyzing complex experiments or leveraging causal inference designs
  • Experience with distributed tools such as Spark, Hadoop, etc.
  • A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)