Senior Quant Analytics — Fraud Risk & GenAI Solutions

Next Frontier Capital; Columbus (OH); On-site; USD 110,000 - 140,000; Full time

Job summary

Chase is seeking a Senior Quantitative Analytics Associate in Fraud Risk to use advanced analytics to prevent plastics fraud and optimize risk/reward tradeoffs in Columbus, OH. The role involves cross-functional collaboration, model development, and delivering data-driven recommendations.

The position requires an advanced quantitative degree and 3+ years of risk-related experience. The candidate will implement GenAI/LLM projects with Python and communicate insights to leadership.

Qualifications

• Advanced degree in a quantitative field (e.g., CS, Math, OR, Data Science).
• 3+ years of experience in Risk Management or any quantitative field.
• Hands-on experience with SQL, Python, and Alteryx.
• Strong understanding of ML algorithms for anomaly detection (clustering, classification, neural networks, time series).
• Experience creating generative AI solutions using LLM prompt engineering and Retrieval Augmented Generation (RAG).
• Experience with evaluation metrics for ML and generative AI.
• Ability to communicate complex concepts to technical and business audiences.

Responsibilities

• Analyze large datasets to detect patterns, trends, and anomalies indicative of fraudulent activity.
• Build and maintain reporting and data automation systems for leadership insights.
• Improve internal analytics techniques and best practices to boost key metrics.
• Collaborate with cross-functional partners from problem identification to data analysis and actionable recommendations.
• Develop and implement GenAI and Agentic AI solutions using Python to automate decision-making.

Skills

SQL

Python

Alteryx

GenAI / LLM

RAG

Communication of results

ML techniques

Education

Advanced degree in Computer Science / Mathematics / OR / Data Science

Tools

Alteryx

Job description

Chase is seeking a Senior Quantitative Analytics Associate in Fraud Risk to use advanced analytics to prevent plastics fraud and optimize risk/reward tradeoffs in Columbus, OH. The role involves cross-functional collaboration, model development, and delivering data-driven recommendations.

The position requires an advanced quantitative degree and 3+ years of risk-related experience. The candidate will implement GenAI/LLM projects with Python and communicate insights to leadership.