Senior Analyst, Cash Flow Underwriting & Intelligence

One Park Financial•Miami, FL

About The Position

One Park Financial (OPF) is a financial technology company that connects small businesses with flexible financing and funding options. The Senior Analyst will own bank-transaction data as an analytical asset and use it to inform approval decisions, portfolio health, pricing, renewals, and growth opportunities. The role covers both risk monitoring and identifying applicants and funded merchants whose cash-flow trends support faster approvals, auto-approvals, pre-approved offers, or proactive renewals. The analyst will work closely with Pricing, Credit, and Data Engineering teams to turn validated signals into operational decisions and trustworthy data pipelines. This is an analysis-and-action role rather than a reporting role: the analyst is expected to assess merchant and segment health, recommend what to do about approvals and pricing, and measure outcomes. OPF also expects analysts to use modern AI and LLM tools to improve analysis and build intelligence into business workflows.

Requirements

5–8 years of experience in data or credit analytics; Financial Services, Lending, or Fintech experience is preferred.
Bachelor’s or Master’s degree in a quantitative field such as economics, statistics, mathematics, finance, or computer science, or a similar field.
Strong SQL and Python skills, including experience working with large datasets and performing analysis in pandas or notebooks.
Fluency with bank-transaction and cash-flow data, including understanding deposits, NSFs, balance trends, data limitations, partial account coverage, seasonality, and survivorship bias in a funded book.
Hands-on experience with Plaid and direct experience working with connected-account transaction feeds, including their structure, quirks, and coverage gaps.
Credit-risk judgment that can distinguish between segments that are struggling and situations that call for tighter criteria, while also identifying cases where the data supports approving more applicants.
Understanding that correlation alone does not determine a pricing decision.
Experience building portfolio-monitoring or performance-tracking metrics, cohort or vintage analysis, and operational dashboards.
Statistical judgment, including validating signals out of sample and accounting for regime shifts and base rates.
Strong business judgment, communication skills, and ability to distill complex analysis for executive audiences.

Nice To Haves

Experience with small-business lending, merchant cash advance, revenue-based finance, or fintech lending.
Understanding of modern AI, including LLMs, agents, and MCPs, and comfort building lightweight tools on proprietary data.
Experience with dbt.
Comfort working in cloud data environments; AWS experience is a plus.

Responsibilities

Analyze merchant financial health using bank-transaction data, including cash runway, deposit velocity, revenue volatility, NSF patterns, and negative-day patterns across applicants and funded merchants.
Build and maintain portfolio health metrics, cohort views, and early-warning dashboards to monitor performance and detect emerging stress.
Identify leading indicators of loss and transaction patterns that precede delinquency, then turn them into monitoring that flags portfolio stress early.
Identify merchants and segments that may warrant approval, faster approvals, auto-approval, pre-approved offers, or proactive renewals; define criteria and partner with Pricing to put them into production.
Use unfunded applicants, including businesses declined by OPF and businesses that declined OPF, as a market signal for industry trends.
Identify industries and segments where pricing may be misaligned with cash-flow trends.
Work with Pricing and Credit teams to translate analysis into approval, offer, and underwriting actions, and measure whether those actions worked.
Partner with Data Engineering on pipelines that keep data clean, current, and trustworthy.
Build lightweight tools and automation, including AI/LLM-assisted workflows, to scale analysis and provide self-service intelligence to operations teams.
Communicate findings to non-technical and executive audiences using clear visuals and narratives.