Hiring.Camp

Data Analyst, Global Growth

Stripe

·
Location
Singapore · Singapore Locations
Department
IT
Education
PhD

Description

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

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 Analyst to partner with our Global organization to drive international expansion and growth. You’ll play a key role in designing and shipping experiments, owning data pipelines, and collaborating with product and engineering teams to establish the right success metrics. You will help track our progress in helping new users to go live on Stripe and empowering existing users to sell globally. Working closely with cross-functional partners, you'll extract actionable insights from Stripe's rich, complex datasets. You will also translate complex business goals into clear analytical frameworks. From building scalable dashboards to crafting compelling data narratives, your insights will directly shape how we run and grow the business.

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

  • Bachelors + 8 years or Masters + 6 years or Phd + 3 years
  • Proficiency in Scala or Python for data pipeline development, not just scripting and SQL
  • Proven ability to manage and deliver on multiple projects with great attention to detail
  • Ability to clearly communicate results and drive impact
  • Experience with workflow orchestration tools (e.g. Airflow, Flyte, or equivalent)
  • Experience with distributed data frameworks such as Spark to write and debug data pipelines
  • Proficiency with AI tools to accelerate model development, analysis, and coding
  • Ability to design, implement, and maintain data pipelines and dashboards to generate actionable insights based on stakeholder requirements
  • Experience collaborating with cross-functional teams to deliver strategic insights, benchmarks, and analyses that provide recommendations
  • Ability to enable stakeholders and partners by building self-service tooling and providing training to empower stakeholder teams to be data literate and self-sufficient in autonomous reporting capabilities

 Preferred qualifications

  • Prior experience at a growth-stage internet or software company
  • Good understanding of development processes and best practices like engineering standards, code reviews, and testing
  • Strong statistical knowledge
  • Working knowledge of Python
  • Experience creating leadership-level reporting, such as QBRs, MBRs

Skills

PythonScalaSQLMachine LearningSparkAirflowData Science

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