Data Scientist
Providence / New York / San Francisco / Remote
Overview
Splitwise is looking for a Data Scientist to join our growing team. At Splitwise, Data Scientists use data to understand how people send and share money, uncover opportunities to improve our user experience and offer new products, and measure the impact of what we ship. 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, statistical rigor, and practical product sense, you’ll unpack that data to learn how people use Splitwise and why. You’ll turn those insights into clear recommendations for our product, engineering, and business teams, helping them monitor changes, investigate key questions, and make better decisions every week.
Our Data team works at the intersection of product analytics, experimentation, business intelligence, and statistical modeling. You might help shape new features by designing and analyzing A/B tests, defining the metrics we rely on to make decisions, building self-serve dashboards that teams use every day, digging into long-term retention and engagement patterns, and developing advanced models in areas such as trust and safety scores, forecasting, and anomaly detection.
You'll collaborate with other data scientists, as well as our product, engineering, and business teams to 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 actually do at Splitwise:
- Design, run, and analyze experiments (A/B tests and similar) to measure the impact of new features and product changes
- Define, implement, and maintain core product metrics, dashboards and reports that reflect how well we’re serving our users
- Dive deep into open-ended questions and turn fuzzy problems into structured analyses and clear recommendations
- Collaborate closely with product managers, designers, engineers, and business stakeholders to prioritize questions, shape experiment designs, and interpret results
- Use SQL and Python to run analyses, prototype models, and build reusable workflows
- Communicate your findings to teammates to help them make informed product and technical decisions
- Contribute to improving our data tools, processes, and best practices as we scale to many more users and teammates
Things about you:
- You enjoy working in a team, and treat others with empathy and respect
- You have strong quantitative and analytical skills, a solid understanding of statistics, and the curiosity to dig deeper when needed
- You're comfortable writing SQL to query large datasets and dig into crosstabs to answer complex questions
- You have the ability to write code in a scripting language (Python, R, etc.) to wrangle data, run analyses, and create useful visualizations
- You’re able to translate ambiguous product or business questions into concrete analytical tasks, and you care about picking the right metric or method for the problem
- You have strong collaboration and communication skills, and can work with product managers, designers, engineers, and business leaders on both technical and strategic topics
- You value intellectual honesty and are transparent about uncertainty, limitations, and alternative explanations in your work
- You have at least a Bachelor’s degree in Statistics, Math or Applied Math, Computer Science, Physics, Economics, Engineering, or a related field, or equivalent experience
- Things that are not required but highly valued: past role on a Data or Analytics 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 cool or impactful data science project you can share with us
Things you’ll learn:
- How to empower data-hungry teammates to answer their own questions with reliable self-serve tools
- How to shape product strategy by turning messy real-world questions into structured analyses and experiments
- How to support strategic decisions in consumer social finance using quantitative research
- How to build and maintain dashboards that become critical to product and business operations
- How to assess product changes through a mix of qualitative and quantitative evidence and research
- How to think about trust & safety, fraud, and business operations through a statistical and product lens
- How a small, transparent start-up operates
Compensation range:
- $130,500 - $184,000/yr base cash compensation
- Depends on experience level and tenure
Benefits:
- Competitive base salary
- Equity/stock options
- Top-tier health care (covered 100% for you, 50% for dependents)
- Dental and Vision insurance
- Unlimited/flexible PTO (most employees take 4-6 weeks)
- Paid parental leave (12+ weeks)
- 401k with match
- Flexible hours (with meeting hours generally from 10am-5pm ET)
- Professional development budget for conferences or other paid resources, in consultation with your manager
- Periodic annual retreats and face-to-face visits with colleagues
- Support for in-office, co-working, or remote work, each with related benefits to do your best work
Application Guidelines
When applying for this position, please email jobs@splitwise.com from your personal email.
Please include an attached resume and concise (1-4 sentences) answers to the following questions in your application email:
Splitwise is headquartered in Providence, RI and has a strong presence in New York, NY. We also support hybrid arrangements with regular visits to these locations, as well as fully remote roles within the USA. Which of these 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, dashboards, and forecasting (B) exploratory product analytics investigating product-related topics, (C) statistical inference and designing product experiments, (D) algorithms, machine learning, and statistics-based product features, and (E) generative AI and LLMs. Please rank these areas of focus in order of personal interest from most interested (1) to least interested (5).
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.