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Data Analyst I

Parker Group · 合规/托管/其他 · 上架 2026-07-27
面议
数据/AI中级📍 India远程

职位要求 / 描述

ABOUT THE ROLE: Parker’s mission is simple but ambitious: to increase the number of financially independent people. We believe the best way to achieve this is by equipping independent business owners with the financial tools they need to scale profitably. Our core product combines a virtual corporate card with profitability-focused financial software, empowering eCommerce merchants to grow faster while maintaining control of their margins. We’ve raised over $180M in equity and debt from world-class investors, including Valar Ventures, Y Combinator, SVB, and notable founders such as Solomon Hykes (Docker), Paul Buchheit (Gmail), Paul Graham (Y Combinator), and Robert Leshner (Compound). We’re a Series B fintech scaling rapidly with strong product-market fit, a growing customer base, and a team driven by technical excellence and real-world impact. We are looking for an exceptional Data Analyst I with strong technical fundamentals, sharp business intuition, and a high bar for quality. You will work most closely with the Risk team (credit, fraud, AML, portfolio analytics), but your impact will extend across the entire company. This role is designed for someone early in their career who is keen on operating with a senior level of ownership and judgment. This is a full-time role at Parker (not a contractor role). Why This Role Matters: - This is not a reporting-only or ticket-driven analyst role. - This is a foundational analytics hire who will help shape how Parker uses data across Risk, Credit, Fraud, Product, Growth, and Finance. You will define how key business and risk questions are measured and turn open-ended questions into durable high-quality analytical systems. - If you want a role where you own important problems end-to-end and your work directly influences capital allocation, credit decisions, and growth strategy — this is it. What You’ll Do: - 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 & AML, portfolio performance, unit economics, and growth - Build automations and data pipelines using SQL and Python (or similar) - Partner closely with Risk, Product, Growth, Finance, and Compliance leaders on high- - impact initiatives - Turn messy, ambiguous questions into clean data, clear metrics and actionable insights - Perform and own business-critical compliance reporting activities for the Risk team Required Skills and Qualifications: - Excellent command of SQL (you can reason about performance, not just write queries) - Strong ability to write Python or similar for data workflows and automation - Strong mental model of data modeling, tables, schemas, and joins - Demonstrated ability to break down ambiguous problems, decide what should be - measured, and build clean, reliable outputs - AI-first approach to create practical applications using Gen AI and LLMs - High ownership mindset: we want you to write your specs and not wait for them - Strong business judgment and curiosity about how companies actually operate - High standards for clarity, correctness, and simplicity - No prior fintech or credit experience is required, but you must show the ability and desire to learn complex domains quickly. Nice To Have: - 1–3 years of experience in analytics, data, or technical roles - Experience in fintech, payments, lending, or financial services - Prior work in credit, fraud, risk, or financial analytics - Experience using statistical or data science libraries - Experience with LLMs or AI-assisted analytics / automation workflows What You’ll Get: - Competitive salary - Equity (ESOP) in a fast-growing fintech company - A role with real ownership and real consequences - Direct exposure to credit strategy, risk management, capital allocation, and business - and growth strategy - The chance to build analyt

技能关键字

#Python#Docker#SQL#AML/KYC#合规

职责方向

团队管理性能/容量部署发布自动化合规风控数据分析

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Data Analyst I · Parker Group
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