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Data Scientist at Splitwise (Providence, RI)

Splitwise is hiring its first full-time Data Scientist! At Splitwise, you’ll help us analyze data about our applications to discover key insights about user behavior. This work will drive future product decisions and inform Splitwise’s product roadmap. The most important product and business decisions we make at Splitwise have always been informed by what we learn from our users. With your help, we can improve Splitwise for our millions of users around the world.

Splitwise is a large consumer app that handles many millions of interactions per day. Using a combination of analytical thinking and statistical rigor, you’ll unpack that data to learn more about how people use Splitwise and why, and pass on that knowledge to our product and engineering teams to help them monitor changes, investigate key questions, and make better decisions.

Typical work for this role will include a mix of Business Intelligence reporting (cohort-based analyses of engagement and retention), ad-hoc observational product research (“how often do people settle debts and why?”) and statistical inference / experiments (ex: A/B tests). There is also some opportunity for Data Science algorithm-based or machine learning projects, but this will not be the initial focus of your work.

This job reports to the CEO, Jon. You’ll collaborate with engineers to ensure that our data pipeline works smoothly and efficiently, and collaborate with product managers and designers to inform future development. We’re a small team of about 10 people, and we’re excited to have you join us!


  • Instrument dashboards, monitoring tools, and reporting structures to empower other teams

  • Dive deep into open-ended product questions to define metrics for success, product expectations, and observational and experimental frameworks for measuring improvements

  • Collaborate with product managers, engineers, and business teammates on technical challenges (ex: the data pipeline) and non-technical issues (ex: product goals)

  • Validate, normalize and reduce data in our data warehouse for consistency and accuracy

  • Measure the impact of new features and experiments

  • Work with industry-standard business intelligence tools like Redshift and Tableau

  • Use SQL and/or scripting languages (R, Ruby, Python, etc.) to run custom analyses

  • Communicate your findings to teammates to help them make informed product and technical decisions


  • You have past work experience in an analytical role on a Growth, Marketing, or Product team.

  • You have very strong quantitative and analytical skills, and a good working grasp of statistics (and the ability to learn in areas where you aren’t an expert).

  • You can use SQL to query a database and dig into crosstabs to answer tricky questions.

  • You have some ability to program basic scripts for running data analyses (which programming language doesn’t matter so much).

  • You have strong collaboration skills. You can work with product managers, designers, software engineers, and business leaders on both technical issues (data pipeline problems or query performance) and non-technical issues (user personas or business impact).

  • You care about your work for its practical impact and who it helps – not just research for its own sake, or trying the latest new tools.

  • You highly value intellectual honesty with your peers, and prefer to be transparent and apolitical about the strengths and weaknesses of your research and possible interpretations.

  • You're willing to come join us at our office in Providence, RI. (If you're not from around here, we can help you move!)

  • You have at a 4-year Bachelor's degree in Statistics, Applied Math, Math, Computer Science, Physics, Economics, Chemistry, Biology, Neuroscience, or another quantitative field, or equivalent

  • Valued but not required: experience at a large consumer technology company, advanced statistical expertise, a relevant Masters or PhD, big data experience, software engineering experience, a machine learning background, a cool or impactful data science project you can share with us


  • How to best empower data-hungry teammates who need to answer their own questions

  • How to take a messy real-world product question and find concrete data to help answer it

  • How to build a data science dashboard that becomes a critical part of business operations

  • How to make product design decisions through a mix of qualitative and quantitative evidence and research

  • How a small, transparent start-up operates

by via developer jobs - Stack Overflow

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