Staff Data Scientist, Growth

N/A

Applications have closed

Stripe

Stripe powers online and in-person payment processing and financial solutions for businesses of all sizes. Accept payments, send payouts, and automate financial processes with a suite of APIs and no-code tools.

View company page

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

The Growth Data Science team helps businesses accelerate their journey to accept payments on Stripe, and find the financial products they need to grow their business. We achieve our goals through experimentation, forecasting, attribution modeling, personalization and algorithmic recommendations. We partner with Marketing, Sales and Self-Serve Product teams to develop intelligent data products and insights, and create go-to-market strategies to drive product discovery, adoption and retention.

What you’ll do

Responsibilities

  • Provide direction to Marketing and Sales on business strategy and optimal resource allocation by establishing robust, systematic solutions to ROI measurement problems. This may include, but is not limited to experimentation, causal inference, marketing mix and attribution modeling.
  • Design and improve predictive models used to set business targets and deliver actionable signals to sales and marketing field teams.
  • Provide senior technical direction to teams on horizontal technical areas, including experimentation, attribution, forecasting, and observability. Assume hands-on leadership, especially when helping teams set their long-term vision and resolve complex problems through iterative execution.
  • Identify broad company problems and opportunities that can be tackled through data science; develop evidence of the validity and utility of data science solutions (e.g. through prototypes or MVP); work with relevant teams to design and build the data science components that deliver outsized value to our users and our business.
  • Contribute to the overall strategy, roadmap, and vision of the Growth DS team.
  • Evangelize and inspire best practices across data science; lead by example to build a culture of craftsmanship and innovation.
  • Provide mentorship to our data science talent to help them grow technically and professionally.

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

  • 10 years of Data Science experience OR equivalent combined work and academic experience in a quantitative field.
  • A PhD or MS in a quantitative field (e.g., Statistics, Economics, Sciences, Engineering).
  • Demonstrated experience of leading organization-wide initiatives spanning multiple teams, or leveraging deep domain expertise to influence tech roadmap planning and execution.
  • Demonstrated ability to effectively collaborate across multiple teams and stakeholders to drive business outcomes 
  • Demonstrated ability to balance execution and velocity with research, statistical depth, and scalable design.
  • Experience, mentoring, and investing in the development of scientists, engineers, and peers.

Preferred qualifications

  • Experience working with Marketing, Sales and/or Growth teams.
  • Experience in the development and implementation of machine learning, statistical or forecasting frameworks
  • Experience with experiment design and causal inference
  • Experience in building and supporting data products end-to-end
  • Experience thinking about user experience, and complex systems
  • Experience with creating alignment with stakeholders in ambiguous and complex situations
  • Experience developing and deploying metric frameworks

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Causal inference Economics Engineering Machine Learning MVP PhD Research Statistics

Perks/benefits: Career development

Region: North America
Job stats:  11  4  0

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.