Financial institutions process billions of transactions every day across cards, ACH, wires, and third party aggregators. But most of that data is difficult to use. Descriptions are inconsistent, merchant names don’t match, and categories vary by payment type.

Spade’s API takes these raw, messy transactions, and in <50 ms, returns clean, structured records linked to verified businesses in our proprietary database. Building on that foundation, our agent layer leverages this enriched data to automate insights and decision-making. Customers including Stripe, FIS, Bilt, Corpay, and Mercury use Spade to authorize more transactions, personalize experiences, power rewards programs, and more. We lead the market in merchant coverage, speed of enrichment, and data accuracy, enriching hundreds of billions of dollars in transaction volume every month.

Spade is a fast growing, Series A company backed by industry experts and top tier investors (including a16z, Flourish Ventures, Y-Combinator, and Gradient Ventures). We’re a lean and execution-oriented hybrid team, passionate about building exceptional products for our growing customer base. We care deeply about diversity of background, experience, and opinion. We value empathy, curiosity, and passion, and strive to create an environment where individuals have autonomy and the ability to take ownership over their work.

What will you be doing?

At Spade, data isn't just what we work with—it's our product. As a Senior Data Scientist, you’ll be delivering real-time insights that transform how financial institutions understand and act on transactions. Using our proprietary merchant, location, and transaction datasets, you'll build across the full ML spectrum—from traditional ML and NLP to AI agents—and work directly with engineering and product to turn ideas into scalable solutions.

You will:

Own ML/AI products end-to-end—from problem framing and prototyping to deployment, monitoring, and iteration
Develop and productionize ML/AI models for entity resolution, data enrichment, and quality improvements
Design and maintain end-to-end data workflows, pipelines, and testing frameworks for production systems
Collaborate with engineering, analytics, and product teams to to translate ambiguous problems into shipped features
Use customer insights and internal metrics to identify new opportunities within Spade’s transaction data
Partner with leadership to define data science strategy, roadmaps, and best practices

What experience, skills, and qualifications are necessary?

Must have:

5+ years of industry experience in data science or machine learning
Bachelor’s degree in a relevant field
Deep expertise in machine learning, statistical modeling, deep learning, and entity resolution
Fluency in Python (including ML/statistical libraries) and SQL
Experience in high-growth startup environment

Nice to have:

Experience in fintech, particularly with payments or transaction-level data
A Master’s or Ph.D. in data science, machine learning, statistics, or another quantitative field
Experience with PySpark and Databricks

Salary Range:

At Spade, we view total compensation as consisting of salary + equity + benefits. We recruit motivated and high performing talent, and work to compensate people in line with the value they bring to our team.
We aim to pay fairly and competitively, and consider a number of factors in developing compensation offers. These factors include years and breadth of experience, interview performance, market dynamics, and internal equity.
The anticipated cash salary range for this role is $180,000-$210,000, and an equity grant will also be provided.

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