Finance Data Analyst

At ClarityPay, we're redefining the point-of-sale credit market to bring more value to merchants. Based in NYC and Atlanta, our fast-growing fintech empowers large merchants with configurable “Pay-Over-Time” tools— including monthly installments, BNPL, and revolving products. We solve complex credit challenges with speed, precision, and intelligence—combining deep expertise with advanced tech to deliver better outcomes, every time.

Our clients rely on us to help them serve their customers, grow, and build loyalty. Our values guide everything we do: we put merchants first, stay data-driven, always know the why, learn relentlessly, and win together as a team. This clarity of purpose fuels our commitment to delivering exceptional customer experiences at speed and scale.

ClarityPay's point-of-sale financing empowers merchants to control commerce flows, convert more customers, and drive growth. Our tailored credit solutions offer flexible, segmented programs across the credit spectrum, equipping merchants with the tools to optimize customer value while delivering a seamless, transparent user experience. We go further to adapt to merchant needs—so they can do more for their customers.

Having recently closed our Series A, we are scaling our operations and building the financial infrastructure to support our next phase of growth. This is an opportunity to join at a foundational moment and help shape how we use data to drive decisions.

We are looking for a Finance Data Analyst to serve as the data engine for our finance team. You will work closely with the Product, Risk, and Finance teams to write and run SQL queries, build datasets, and surface insights that drive financial reporting, portfolio analysis, and business decisions. This is a highly cross-functional role — you sit at the intersection of data, credit, and finance, and your work will directly inform how we manage and grow the business.

Data Extraction & Analysis

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  Write, optimize, and maintain complex SQL queries to extract and analyze data across loan originations, portfolio performance, payment activity, and merchant transactions

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  Build and maintain clean, reliable datasets and data pipelines to support recurring finance and risk reporting

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  Perform ad hoc analyses to answer business questions across the credit, product, and finance teams

Financial & Portfolio Reporting

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  Support the finance team with data pulls for monthly reporting, investor updates, and board materials

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  Analyze portfolio-level metrics including origination volumes, delinquency rates, loss rates, prepayment speeds, and cohort performance

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  Build and maintain dashboards in BI tools (Looker, Tableau, or similar) to give stakeholders real-time visibility into key metrics

Product & Risk Collaboration

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  Partner with the Risk team to pull and analyze credit performance data, underwriting outcomes, and loss trends

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  Work with the Product team to instrument new features, track performance metrics, and assess the financial impact of product decisions

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  Translate raw data into clear, actionable insights for non-technical stakeholders

Data Infrastructure

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  Use Python to automate recurring data pulls, reporting workflows, and manual finance processes to improve efficiency and reduce operational overhead

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  Partner with engineering to understand data models, ensure data quality, and flag anomalies

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  Help build and document a scalable data foundation for the finance function

• Bachelor's degree in Finance, Economics, Statistics, Computer Science, or a related field

• 2–4 years of experience in a data analyst, financial analyst, or similar role

• Strong SQL skills — comfortable writing complex queries, joins, window functions, and aggregations

• Proficiency in Python for data analysis and process automation (pandas, numpy)

• Experience with BI tools such as Looker, Tableau, or Power BI

• Familiarity with consumer lending, fintech, or financial services data is a strong plus

• Ability to work cross-functionally and communicate data findings clearly to finance, risk, and product stakeholders

• Detail-oriented, intellectually curious, and comfortable working in a fast-paced startup environment