# Data Analyst I

**Company:** [Parker](https://hotfix.jobs/companies/parker)
**Location:** Remote
**Role:** Data Analytics
**Salary:** $22k – $36k/yr
**Skills:** SQL, Python, Data Modeling, Data Pipelines, Dashboards, Generative AI, LLMs, Credit Risk, Fraud Analytics, AML, Portfolio Analytics, Data Science Libraries
**Posted:** 2026-01-23

> Builds analytical metrics, dashboards, automations, and reporting systems for risk and broader business decisions. The role requires strong SQL and Python skills, sound data modeling, business judgment, and the ability to solve ambiguous problems independently.

## Job Description

## Responsibilities
- Design, build, and own core analytical metrics and dashboards used by leadership and operating teams.
- Analyze transaction, customer, and credit data to drive decisions across credit risk, fraud and AML, portfolio performance, unit economics, and growth.
- Build automations and data pipelines using SQL and Python or similar tools.
- Partner with Risk, Product, Growth, Finance, and Compliance leaders on high-impact initiatives.
- Turn messy, ambiguous questions into clean data, clear metrics, and actionable insights.
- Own business-critical compliance reporting activities for the Risk team.

## Requirements
- Excellent command of SQL, including query performance reasoning.
- Strong ability to write Python or similar code for data workflows and automation.
- Strong understanding of data modeling, tables, schemas, and joins.
- Ability to break down ambiguous problems, determine what should be measured, and build clean, reliable outputs.
- AI-first approach to creating practical applications with generative AI and LLMs.
- High ownership mindset and ability to write specifications independently.
- Strong business judgment and curiosity about how companies operate.
- High standards for clarity, correctness, and simplicity.
- Ability and desire to learn complex domains quickly.

## Nice-to-haves
- 1–3 years of experience in analytics, data, or technical roles.
- Experience in fintech, payments, lending, or financial services.
- Experience in credit, fraud, risk, or financial analytics.
- Experience with statistical or data science libraries.
- Experience with LLMs or AI-assisted analytics and automation workflows.

## Compensation and Benefits
- Competitive salary.
- Equity (ESOP) in a fast-growing fintech company.
- Real ownership and exposure to credit strategy, risk management, capital allocation, and business and growth strategy.
- Opportunity to build analytics systems from early stages.
- Work on applied AI and LLM-driven analytics and automation.
- Increasing scope and responsibility over time.

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