Senior Analyst, Cash Flow Underwriting & Intelligence

One Park Financial; Miami (FL); On-site; USD 95,000 - 140,000; Full time

Benefits offered by this job

Competitive salary

Health Insurance

Dental & Vision Insurance

401k with Match

Identity Protection

Life Insurance

PTO & Holidays

Growth Opportunities

Team Events

Company Culture

Job summary

One Park Financial in Miami is seeking a Senior Analyst to own bank-transaction data as an analytical asset and turn it into decisions on approvals, pricing, and renewals.

You will monitor portfolio health, build dashboards, and identify leading indicators of loss while collaborating with Pricing and Credit to push faster, smarter offers.

This role emphasizes AI-forward analytics and the ability to explain complex signals to executives, helping the company scale its data-driven lending.

Qualifications

• 5-8 years of experience in data or credit analytics.
• Bachelor's or Master's in economics, statistics, mathematics, finance, computer science, or similar.
• Strong SQL and Python; comfortable pulling large datasets and performing analysis.
• Fluency with bank-transaction / cash-flow data and understanding data limitations.
• Hands-on experience with Plaid.
• Credit-risk instinct balancing approvals with tightening.
• Experience building portfolio-monitoring metrics, cohorts, and dashboards.
• Statistical judgment and out-of-sample validation.
• Excellent business judgment and executive communication.
• Fintech lending or small business finance experience is a plus.
• Knowledge of AI/LLMs and lightweight tooling is a plus.
• Experience with dbt and AWS is a plus.

Responsibilities

• Own the read on merchant financial health from bank-transaction data across applicants and funded merchants.
• Monitor portfolio health metrics, cohorts, and dashboards to show performance and drift.
• Identify leading indicators of loss and turn them into proactive monitoring.
• Find whom to approve faster and build the case for auto-approval, pre-approved offers, and renewals with Pricing.
• Use declined applicants as a market signal to gauge industry direction.
• Surface pricing opportunities where mispricing occurs relative to cash-flow reality.
• Translate signals into action with Pricing and Credit and measure outcomes.
• Partner with Data Engineering to keep data clean and trustworthy.
• Build lightweight AI/LLM-assisted workflows to scale analysis.
• Communicate findings clearly to non-technical and executive audiences with visuals.

Skills

SQL

Python

Bank data

Data analysis

Plaid

Education

Quantitative degree

Tools

Plaid

Job description

Company Overview:

One Park Financial (OPF) is a leading Financial Technology company dedicated to empowering small businesses by connecting them with flexible financing and funding options. Our mission is to provide entrepreneurs with the working capital they need to elevate their businesses. At OPF, we believe in working with high-performing individuals who are ready to play an integral part in our company's expansion — because our success hinges on our people.

Why Join Us?

At OPF, we foster a dynamic and inclusive company culture that emphasizes collaboration, innovation, and personal growth. Our team is composed of passionate, driven individuals who are committed to making a difference. Here’s what you can expect when you join our team:

• Innovative Environment: Work with cutting-edge technology and be part of a team that is constantly pushing the boundaries of fintech.
• Professional Growth: We invest in our employees’ growth with continuous learning opportunities, training programs, and career advancement paths.
• Supportive Culture: Enjoy a supportive and inclusive work environment where your ideas are valued, and your contributions make a real impact.
• Community Focus: Be part of a company that understands the importance of small and mid-sized businesses to their communities and the nation’s financial health.
• High-Performing Team: Join a team of badasses who are committed to excellence and are integral to our company's expansion and success.

About the Role

We fund small businesses, and the richest thing we know about them is their bank activity. Every applicant and every merchant we fund connects their accounts, which gives us deposits, balances, withdrawals, NSFs, and revenue trends on tens of thousands of businesses every week. Most of that signal is not yet used.

We are looking for a Senior Analyst to own that data as an analytical asset and turn it into decisions: who we should approve and how fast, where the portfolio is heading, and the growth we're currently leaving on the table.

This cuts both ways, and that's what makes the role bigger than credit. On defense, you'll continuously monitor the health of the portfolio and find the cash-flow patterns that move weeks ahead of losses. On offense, you'll find the merchants whose bank data says we should be saying yes, and saying yes faster: the businesses with strong, steady trends who are prime candidates for auto-approval, pre-approved offers, and renewals. You'll use the applicants we don't fund as a market signal, and you'll work directly with our Pricing and Credit teams to turn all of it into action.

This is not a reporting role. You'll be the person who can answer, straight from the data, "is this segment getting healthier or weaker, who in it should we be approving, and what should we do about pricing and renewals?"

We are a very AI-forward company, and we expect our analysts to work that way. We want someone who leans on modern AI and LLM tooling to make their own analysis faster and sharper, and who is excited to help build intelligence directly into how the business runs.

We want to work with high-performing badasses who see the whole picture and make everyone around them better.

Responsibilities

• Own the read on merchant financial health from bank-transaction data (cash runway, deposit velocity, revenue volatility, NSF and negative-day patterns) across both applicants and funded merchants.
• Own ongoing portfolio monitoring: build and maintain the health metrics, cohort views, and early-warning dashboards that tell us how the book is performing and where it's drifting, so the business sees stress building before it shows up in the numbers.
• Find leading indicators of loss, segments where transaction trends move weeks ahead of delinquency, and turn them into monitoring that flags stress before it hits the portfolio.
• Find where we should be growing: identify the merchants and segments whose cash-flow trends say we should approve them, and build the case to say yes faster, including candidates for auto-approval, pre-approved offers, and proactive renewals. You'll define the criteria and partner with Pricing to put them into production.
• Use the applicant pool we don't fund as a market signal: businesses we declined and businesses that declined us are a less biased read on where industries are heading than our own book.
• Surface pricing opportunities: industries and segments where we're mispriced relative to their cash-flow reality, in either direction.
• Translate signals into action with the Pricing and Credit teams (faster approvals and better offers in strengthening segments, tighter criteria in weakening ones) and measure whether the actions actually worked.
• Partner with Data Engineering on the pipelines that keep this data clean, current, and trustworthy.
• Build lightweight tools and automation, including AI/LLM-assisted workflows, to scale the analysis and put self-serve intelligence in the hands of the operations teams.
• Communicate findings clearly to non-technical and executive audiences with clean visuals and a clear story.

• 5-8 years of experience in data or credit analytics, preferably in Financial Services, Lending, or Fintech.
• Bachelor's or Master's degree in a quantitative field (economics, statistics, mathematics, finance, computer science, or similar).
• Strong SQL and Python skills; comfortable pulling large datasets and doing the real analysis in pandas/notebooks.
• Genuine fluency with bank-transaction / cash-flow data. You know what a deposit, an NSF, and a balance trend actually tell you about a business, and where the data can mislead you (partial account coverage, seasonality, survivorship bias in a funded book).
• Hands‑on experience with Plaid. You've worked directly with connected‑account transaction feeds and understand their quirks, coverage gaps, and how the data is structured.
• A credit-risk instinct that runs both ways: you can separate "this segment is struggling" from "we should tighten," and you can spot where the data says we should be approving more, not less. You know a correlation is not a pricing decision.
• Experience building portfolio-monitoring or performance‑tracking metrics, cohort/vintage analysis, and dashboards that a business actually runs on (not one‑off reports).
• Statistical judgment. You validate a signal before you trust it (out‑of‑sample, regime shifts, base rates) rather than chasing the strongest correlation.
• Excellent business judgment and communication, and the ability to distill complex analysis for executive audiences.
• Experience with small‑business, merchant cash advance, revenue‑based finance, or fintech lending (a strong plus).
• A real understanding of modern AI (LLMs, agents, MCPs) and comfort building lightweight tooling on your own data (a plus).
• Experience with dbt (a plus).
• Comfort with cloud data environments (AWS a plus).

• Competitive salary
• Local & National Health Insurance
• Dental and Vision insurance
• Group Medical Bridge
• 401k with Match
• ID Protection: 100% covered by the company
• Life Insurance: 100% covered by the company
• Generous PTO and holidays
• Growth and development opportunities
• Dynamic and collaborative work environment
• Company events and team-building activities