Data Scientist, Growth

Stripe (View all Jobs)

Canada

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Interview Process

1. Programming/debugging phone screen 2. On-site with your own laptop/setup and full access to internet. Interviews include systems design, 45 min practical coding question, integrating an API exercise, debugging, and talking with hiring manager about team alignment.

Programming Languages Mentioned

Python, SQL


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

At Stripe, we’re dedicated to helping millions of companies worldwide to find the financial products they need to grow their businesses. That’s why our Growth Data Science team creates intelligent data products and insights to help us deliver the right message to the right user at the right time. We collaborate with Marketing and Sales to influence the go-to-market strategy, boost product adoption, and increase user retention by making data-driven decisions at scale.

What you’ll do

We’re looking for a Data Scientist to partner with the Marketing team to improve the performance and target efficiency of marketing performance across channels (e.g. email, website, events, paid search) and across funnels (e.g. self-serve, sold), develop attribution models, and generate insights to inform data-driven go-to-market strategy.

Responsibilities

  • Apply statistical, machine learning and econometric models on large datasets to measure performance, and identify the causal impact of marketing campaigns.
  • Develop attribution models, and generate insights into what campaigns and channels are most effective from the attribution model.
  • Develop predictive lead scoring to identify the target audience for marketing and sales campaigns.
  • Design, analyze, and interpret the results of experiments. Drive the collection of new data and the refinement of existing data sources.
  • Partner closely with Marketing, Sales, Finance, Engineering and Product teams to identify and address the most impactful challenges with data and analyses.

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

  • 6+ years of data science/quantitative modeling experience.
  • A PhD or MS in a quantitative field (e.g., Statistics, Economics, Sciences, Engineering).
  • Strong knowledge of statistics, machine learning, and experiment design.
  • Proficiency in Python and SQL.
  • Experience with data-distributed tools (Scalding, Spark, Hadoop, etc).
  • A demonstrated ability to manage and deliver on multiple projects with a high attention to detail.
  • Ability to communicate results clearly and a focus on driving impact.
  • Experience working with cross-functional teams to deliver results.

Preferred qualifications 

  • Experience designing and developing statistical modeling or machine learning pipelines.
  • Experience working with Marketing and/or Growth teams.

Please mention No Whiteboard if you apply!
I'm a one-man team looking to improve tech interviews, and could use any support! 😄


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