Providence, Boston, New York, Remote
Splitwise is looking for a Data Scientist to join our growing team. At Splitwise, Data Scientists 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. You’ll be helping tens of millions of people manage money with their friends and family and reduce the stress that sharing costs places on relationships.
Splitwise is a large consumer app that handles 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.
Splitwise uses data in many ways and members of the Data Team work on 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?”), statistical inference / experiments (such as A/B tests), and statistical algorithm-based projects (anomaly detection, trust and safety scores, etc).
This job reports to the CEO, Jon Bittner. You'll collaborate with engineers (as well as our product and business teams) to implement new features and help Splitwise scale on our journey to 100 million+ users. We're currently a small team - and you can make a huge difference.
What you’ll do at Splitwise:
- 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 (such as data pipelines) and non-technical issues (for example prioritizing product goals)
- Validate, normalize and clean data in our data warehouse for consistency and accuracy
- Measure the impact of new features and experiments
- Work with industry-standard business intelligence tools built on relational databases and event pipelines, as well as purpose-built in house tools
- Use SQL and scripting languages (R, Python, Ruby, etc.) to code and run custom analyses
- Communicate your findings to teammates to help them make informed product and technical decisions
Things about you:
- You enjoy working in a team, and treat others with empathy and respect
- 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 complex questions
- You have some ability to program basic scripts for running data analyses (language doesn’t matter so much, we use a mix of R, Python, and Ruby) and to create useful data visualizations
- 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 the practical impact of your work and who it helps – not just research for its own sake, or trying the latest trendy new tools or packages
- 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 have at least a Bachelor's degree in Statistics, Math or Applied Math, Computer Science, Physics, Economics, Chemistry, Biology, Neuroscience, Psychology or similar field, or equivalent
- Things that are not required but highly valued: past role on a Data or Strategy team; experience at a tech company (especially a consumer tech company) on the Growth, Marketing, or Product teams; advanced statistical expertise; a PhD or Masters in a relevant field; software engineering experience; a machine learning background; a cool or impactful data science project you can share with us
Things you’ll learn:
- How to empower data-hungry teammates who need to answer their own questions
- How to take a messy real-world product question and find data that helps answer it
- How to support strategic decisions in social finance through primary research
- 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 to think about trust-and-safety, fraud, and operations through a statistical lens
- How a small, transparent start-up operates
Please include an attached resume and concise (1 - 4 sentences) answers to the following questions in your application email:
Splitwise is based in Providence, and is hiring locally at our Providence HQ, as well as in Greater Boston, New York City and remotely within the USA (for candidates that are eligible to work in the US). We are also happy to relocate interested candidates to Providence. Which of these location options are you interested in?
What interests you about working with Splitwise specifically?
Data Science as a title can mean many different things at many different companies. Some distinct areas of focus are (A) business intelligence reporting and dashboards, (B) exploratory product analytics investigating product-related topics, (C) statistical inference and designing product experiments, and (D) algorithms, machine learning, and statistics-based product features (such as a recommendation engine). Please rank these areas of focus in order of personal interest from most interested (1) to least interested (4).
In a few brief sentences, describe an interesting piece of data analysis work you’ve done in the past, and summarize the most important conclusion or impact from that work. (You may optionally also share a link to a summary, journal article, blog post or code for this analysis, if one is available.)
Consider a mobile app that you often use and are familiar with (ex: Gmail on Android). Briefly propose a product change you believe could be valuable for that product, and explain how you would test if that product change was effective.
Splitwise is an equal opportunity employer that cares deeply about diversity in tech, and we strongly encourage candidates from all backgrounds to apply. We want to build a team at Splitwise that reflects the diversity of customers that we serve, and we hope that team includes you! Join us in our mission to reduce the stress that money places on relationships, and help millions of friends and families around the world.
- Competitive salary
- Equity/stock options
- Top-tier health care (covered 100% for you, 50% for dependents)
- 4-6 weeks of vacation per year
- 12+ weeks of parental leave (either parent, or adoption)
- 401k with match
- Flexible hours (generally 10am-5pm ET)
- Free parking or transit benefits
- Sponsored tickets to industry conferences
- Choice of work laptop and desk
- Paid team meals when in office
- Relocation benefits
- Dental and vision plans available
Interested? Contact us at email@example.com.
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