AI-Driven Risk Data Scientist

Giggle Finance; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Giggle Finance is seeking a data‑driven analytics professional to join the Risk team. You will tackle high‑impact problems, build predictive models for underwriting and fraud detection, and leverage AI to accelerate research and development.

The role emphasizes learning, collaboration, and delivering production‑ready insights. Ideal candidates have a strong quantitative background, 3+ years in analytics, and comfort translating complex findings into actionable business decisions.

Qualifications

• Bachelor's degree in Statistics, Computer Science, Mathematics, Economics, Engineering, Psychology, Sociology, or other quantitative discipline.
• Master's degree is a plus.
• 3+ years of experience in analytics or data science.

Responsibilities

• Partner with the Risk function to solve high‑impact analytical problems.
• Build predictive models to improve underwriting, fraud detection, pricing, and portfolio performance.
• Use AI to accelerate research, automate analysis, and speed up development.
• Design experiments, A/B tests, and statistical analyses guiding decisions.
• Write production‑quality SQL and develop analytics in Python and/or R, plus Snowflake.
• Transform large datasets into actionable business intelligence and insights.
• Build dashboards, executive reports, and analytical tools for cross‑company use.
• Collaborate with Engineering, Product, Finance, Operations, and Marketing to productionize ideas.
• Constantly ask how to improve decision quality.

Skills

Analytical thinking

Independent learner

Collaborative

Education

Bachelor's degree in Statistics/CS/Math

Master's degree preferred

Tools

SQL

Python

R

Snowflake

Job description

Giggle Finance is seeking a data‑driven analytics professional to join the Risk team. You will tackle high‑impact problems, build predictive models for underwriting and fraud detection, and leverage AI to accelerate research and development.

The role emphasizes learning, collaboration, and delivering production‑ready insights. Ideal candidates have a strong quantitative background, 3+ years in analytics, and comfort translating complex findings into actionable business decisions.