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Giggle Finance is a company focused on serving and empowering the gig economy, which represents over 50% of the U.S. workforce. With advanced technology, exceptional customer service, and a commitment to transparency, Giggle Finance strives to provide financial services to gig workers quickly and efficiently. Their goal is to deliver cash into gig workers' bank accounts in a matter of minutes, helping them take on more jobs, manage unexpected expenses, and address cash-flow needs.

Role Description

We're seeking a Risk Analyst / Data Scientist to join our team and tackle some of the most challenging and high-impact issues facing our business. This is a hybrid role requiring a strong blend of problem solving skills, analytical expertise, statistical modeling skills, and clear / concise communication. You'll be responsible for transforming ambiguous business questions into well-supported, data-driven insights—and articulating your reasoning throughout the process.

You’ll work closely with the Chief Risk Officer (CRO), product leads, and other senior stakeholders to design, build, and communicate insights that shape decision-making across the company.

What You’ll Do :

• Collaborate with business leaders to surface and frame critical risk, credit, and operational questions requiring analytical insight
• Drive end-to-end research initiatives by formulating hypotheses, designing test strategies, sourcing and analyzing data, and delivering actionable conclusions
• Develop tools and models using R or Python; leverage SQL daily to extract, transform, and prepare data for integration into monitoring dashboards and other analytical products
• Communicate findings through well-crafted memos and executive-ready slide decks that clearly articulate insights and recommendations
• Present analysis and strategic guidance to senior leadership, including the CRO and other executive stakeholders
• Work cross-functionally with teams in risk, product, finance, and engineering to operationalize insights and guide the decision-making process.

What We’re Looking For :

• Exceptional problem-solving abilities—you know how to ask the right questions, navigate ambiguity, and develop testable, data-informed approaches
• Proficiency in SQL and either R and / or Python for analytical workflows
• A track record of translating analysis into compelling communication : clear memos, effective slide decks, and confident presentations to senior stakeholders
• Familiarity with experimentation methodologies, including A / B testing frameworks
• Experience—or a strong interest—in developing and evaluating statistical models that guide real-world business decisions
• A keen eye for detail and a dedication to ensuring accuracy in both data and narrative

Ideally :

• Experience in credit risk, fintech, and / or consumer lending
• Comfort working with large, messy datasets in production environments
• Familiarity with BI tools (e.g., Tableau, Looker, Domo, PowerBI) or dashboard development
• Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Economics, Math) or the social sciences (psychology, sociology).
• R or Python proficiency with hands-on experience in a professional setting.
• Familiarity with BI tooling (e.g. Tableau, Looker, Domo, PowerBI)
• 2+ years in a data-centric / quantitative strategy role
• Excellent written and verbal communication skills

Preferred qualifications :

• 4+ years in a data-centric / quantitative strategy role
• 2+ years in a fintech and / or consumer / commercial lending firm.
• Proficiency with one or more BI tools (e.g. Tableau, Looker, Domo, PowerBI)
• Proficiency with both R and Python
• Experience with QA or building credit risk / fraud machine learning models.