Payments Data Analyst $100,000
Remote · Full-time - US Based
If you do not have direct experience with Visa/ Mastercard, BIN / MID data, please do not apply.
About the company
A fast-growing payments optimisation consultancy that helps eCommerce brands scale by getting their payment setups right. In just a few years, it has supported over 2,000 online sellers, saved them more than $15m, and unblocked 400-plus accounts across the major processors. The team is globally distributed across the US, Germany and Mexico, and works with sellers of every size, from early-stage brands to enterprises doing over $100m in online sales.
The role
As a Payments Data Analyst, you'll turn payments and transaction data into insights clients can act on. You'll analyse PSP performance, fraud, chargebacks, reserves and approval rates to find ways to cut risk and grow profit, and build the data models, dashboards and reports that drive payment-strategy decisions across international payment methods, FX optimisation and checkout performance. Day to day you'll pull and clean data from multiple processors, run the analysis, visualise the numbers, and explain what they mean to internal teams and clients. You'll work alongside payment strategists, risk specialists and client success on live consulting projects, shaping recommendations on account setup, optimisation and unblocking.
What you'll bring
- Strong analytical skills, with data analytics and data modeling experience relevant to payments or eCommerce.
- A working grasp of statistics: hypothesis testing, trend analysis, and basic forecasting.
- Clear communication, able to present complex insight to non-technical audiences.
- SQL, Excel or Google Sheets, and at least one visualisation tool (Tableau, Power BI, Looker or similar).
- Experience with payments, eCommerce or financial data (PSP data, gateways, chargebacks, reserves) is a strong plus.
- A degree in a quantitative field (Data Science, Statistics, Maths, Economics or Finance), or equivalent hands-on experience.
- Comfortable working independently in a remote, distributed team, juggling several projects and hitting deadlines.
- Detail-oriented and proactive, with a nose for spotting data issues and opportunities.
The details
Full-time, fully remote. Mid-level, so a strong second move for a data analyst who wants to go deep on payments.
