Product Performance Analyst
Spade
- Location
- New York, NY
- Employment
- Full Time
- Work model
- Remote
- Level
- Senior
- Posted
- 1h ago
Skills
About this role
What is Spade? 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 is a data and AI platform that turns messy transaction strings into structured, verified records — and gives teams the tools to act on it across authorization, attribution, analytics, and AI initiatives. Spade leads the market in terms of merchant coverage, matching accuracy, geolocation data, and speed of transaction enrichment. Customers such as, FIS, Bilt, Mercury, Stripe, alongside many other leaders in fintech and financial services, trust Spade's data to enable personalized rewards programs, accurate applied spending rules, precise analytics requests, and innovative AI-powered features. Spade is a fast growing, Series B company backed by industry experts and top tier investors (including Oak HC/FT, 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? As a Product Performance Analyst, you’ll help drive the quality and performance of Spade’s enrichment products. Working directly with transaction data across card and ACH networks, you’ll analyze product performance, investigate anomalies, and identify opportunities to improve accuracy and reliability at scale. You’ll work closely with product, engineering, and AI/ML data scientists to turn those insights into meaningful improvements for our products and customers. You will: Assess product performance across Spade’s enrichment products by analyzing data quality, accuracy, match rates, and other key performance metrics Investigate anomalies and patterns across large, complex datasets, and drive improvements to the core product and data Define, build, and maintain dashboards, monitoring, and automated alerts that help teams identify issues before they impact customers Identify opportunities to improve QA processes and operational workflows, partnering with internal teams to automate manual work Contribute to and improve quality standards by creating and improving runbooks, documentation, processes, and workflows as Spade’s products and transaction volume grow Partner cross-functionally with Product, Engineering, AI/ML Data Science, and other teams to translate performance insights into improvements across Spade’s product roadmap What experience, skills, and qualifications are necessary? Must have 3–5 years of experience in an analytical role with meaningful exposure to data quality, product analytics, or performance monitoring Strong SQL skills, including experience working with complex joins, aggregations, CTEs, and window functions to analyze large datasets Working proficiency in Python for large data manipulation, metric development, writing scripts to automate recurring analytical tasks Experience building and maintaining BI dashboards and automated monitoring or alerting using tools such as Hex, Looker, Tableau, Metabase, or similar platforms Strong analytical instincts and demonstrated experience finding patterns in messy data A process mindset with experience improving workflows rather than relying solely on one-off fixes Strong communication and collaboration skills, including the ability to communicate effectively with technical and non-technical stakeholders An AI-forward approach to work, using tools such as coding assistants and LLMs to work more effectively Nice to Have Experience with Databricks, PySpark, dbt, or similar data tooling Experience in early / growth stage environment