Techno-Functional Business Analyst, AML Detection
Overview
You will own the AML and fraud detection analytics for a long-term client partnership in financial crime prevention, working from Hoboken, NJ in a hybrid model. Your stack pairs SQL, Python, and Jupyter with deep domain knowledge in anti-money laundering. You will bridge business teams and data engineering, translating regulatory requirements into actionable insights. This role stands out for its direct impact on detecting financial crime at scale.
What You'll Do6
- 1Own end-to-end analysis of AML and fraud detection workflows, mapping business rules to technical requirements.
- 2Build SQL queries and Python scripts to extract, transform, and analyze transaction data for suspicious patterns.
- 3Drive requirements gathering with compliance and operations teams, translating their needs into data models.
- 4Design Jupyter notebooks that document investigative steps and improve repeatability for fraud analysts.
- 5Scale detection logic by partnering with data engineers to implement rule-based and machine learning enhancements.
- 6Lead root-cause analysis on false positives, refining alert thresholds to cut noise without missing true positives.
Requirements6
- 15+ years as a business analyst, with 3+ years focused on AML or fraud detection in financial services.
- 2Proven ability to write SQL for complex joins and aggregations, and Python for data manipulation and analysis.
- 3Hands-on experience with Jupyter notebooks for exploratory data analysis and documentation.
- 4Deep knowledge of AML regulations (BSA, OFAC, KYC) and fraud typologies (transaction laundering, identity theft).
- 5Experience working in hybrid teams, with clear communication across business and technical stakeholders.
- 6Bachelor's degree in finance, computer science, or equivalent; CAMS certification is a plus.
Salary Insight
$114 - $121k per year
Location
Required Skills
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