Senior Data Scientist

Remote /
Engineering /
Full Time
What we do

Pave is building a Cashflow API that allows fintech developers and data scientists to connect their data sources and retrieve clean & unified insights into their consumers’ spending habits, bills, earnings profile, and account health.

We're abstracting the data cleaning and transformation efforts necessary to get a single view of a consumer’s finances so that fintech companies can rapidly build budgeting features, recommendations engines, risk models, and more.

We believe that by lowering the friction of extracting financial insights from the growing number of data sources, we can help accelerate the development of innovative and inclusive financial products. We’re on a mission to enable builders to reinvent and lower the cost of financial services.


There are a growing number of companies helping people gain access to digital financial services, whether it’s low-interest loans, payment installment solutions, integrated insurance offerings, fee-less banking, personalized budgeting, wage advances, or investment solutions.

We believe financial services will exist for every consumer segment, especially underserved segments including female professionals, refugee communities, creators, immigrants, retirees, gig workers, and so forth. We are not original in this thought - this is already happening.

Building equitable financial services for underserved consumer segments requires expensive resources, infrastructure, and analysis into new types of datasets. However, the cost to clean, transform, and analyze these new datasets is high, and every company is forced to do the same bespoke work on the same data sources. This is significant time and cost, and impeding the mission around expanding financial inclusion.

We're 3x founders with a history of launching successful data products, and we're partnered with awesome fintech investors including Bessemer Ventures, Village Global, Better Tomorrow Ventures, 8VC, and execs from Coinbase, Chime, and Sofi.

The Role

At Pave, you will have the opportunity to develop the foundational systems, tools, and processes the next generation of fintech startups are being built upon. We’re constructing the insights layer that lives between raw fintech data sources and the applications ingesting them.

We are looking for a data scientist with a strong background in data infrastructure, ML, and NLP. Our ideal candidate is someone who is eager to build models that are ready to meet the growing needs of our customers. We are forging our platform (scaling from millions of transactions to billions!) and you will have direct influence over the systems and architecture we implement.

On a day to day basis, you will work with our product and engineering teams to develop unique methodologies to solve challenging problems--can we predict account overdrafts? Can we build a loan default risk model? Can we recommend spending budgets for a given user?

The Team

We’re an 10 person team of hungry, mission-driven individuals bent on leveling the playing field of financial services. We’re a small team (though not for long!) looking for someone with strong programming skills to have an active hand in defining our company’s culture.

You’ll be leading data science projects from start to finish, so you should be ready to:

    • Articulate and translate product questions into analysis. You’ll be asked to define the objectives of new analyses you’re conducting and how they get Pave closer to our product goals
    • Dig into the data! Strong data-querying skills (SQL and/or Spark, etc.), classification skills (tagging, etc.), and experience with a scripting language for data processing and development (Python, R, etc.) are a necessity to succeed in this role. Experience with financial data is a plus!
    • Prototype ML models. You’ll have access to vast quantities of data and a blank canvas to construct models the way you’ve always wanted to
    • Explain your decision making process. While we’re technical, we’re not all statisticians, so you should feel comfortable explaining difficult statistical topics and why you chose to implement them
    • Establish performance metrics to evaluate the effectiveness of your projects
    • Push it into production! After all that work, you should be ready to collaborate with engineering to get your model implemented in production

You’ll be a great fit if:

    • You’re a team player, always ready to talk through hard questions and give feedback
    • You’re a self-starter who is eager to get things done
    • You’re excited to be involved in all aspects of the product
    • You’re scrappy! You love proactively finding solutions to problems and you’ve got a get-it-done mindset
At Pave, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, national origin, gender, sex, gender identity or expression, sexual orientation, age, citizenship, marital or parental status, disability, veteran status, or other class protected by applicable law. We are proud to be an equal opportunity workplace.


Who else is on the team?
Pave Bios

Where is Pave located?
We’re building a fully remote team!

How are you funded?
We incubated Pave out of the Village Global accelerator last summer and closed a seed round with BessemerVillage GlobalBetter Tomorrow Ventures8VC, and execs from Coinbase, Chime, and Sofi.