Senior Financial Crimes Analytics Lead - ML & Detection

Raymond James; Saint Petersburg (FL); On-site; USD 130,000 - 190,000; Full time

Job summary

Raymond James is seeking a Manager, Financial Crimes Analytics to design, test, and optimize surveillance models across AML, Fraud, KYC, and Sanctions. This senior individual contributor role combines hands-on model development with technical leadership and cross-functional collaboration.

The candidate will calibrate thresholds, evaluate efficacy, and ensure scalable analytics, partnering with stakeholders, Technology, and Model Risk Management to strengthen detection capabilities.

Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Finance, Business, or a related field.
• Six (6) or more years of experience in financial crimes analytics, model development, data science, quantitative analytics, or related work in financial services, FinTech, or consulting.
• Relevant data science, machine learning, cloud, or financial crimes certifications are a plus but not required.

Responsibilities

• Lead design, testing, and optimization of surveillance models across AML, Fraud, KYC, and Sanctions.
• Develop, test, tune detection scenarios, thresholds, segmentation, and risk scoring.
• Lead ATL/BTL testing, back-testing, and model efficacy assessments to identify gaps.
• Monitor model performance, health indicators, and early-warning processes; investigate deterioration.
• Configure, test, tune, and optimize FCRM, LexisNexis Bridger, and Fenergo platforms; support integrations.

Skills

SQL

Python

Statistics

ML/AI models

Model testing

Education

Bachelor's degree in data science / related field

Tools

Fiserv FCRM

LexisNexis Bridger

Fenergo

Job description

Raymond James is seeking a Manager, Financial Crimes Analytics to design, test, and optimize surveillance models across AML, Fraud, KYC, and Sanctions. This senior individual contributor role combines hands-on model development with technical leadership and cross-functional collaboration.

The candidate will calibrate thresholds, evaluate efficacy, and ensure scalable analytics, partnering with stakeholders, Technology, and Model Risk Management to strengthen detection capabilities.