Staff AML Quant Analyst

Netspend • Austin, TX

2d

About The Position

The Senior Data Scientist – AML plays a critical role developing and supporting Netspend’s Compliance Department, with a specific focus on AML Compliance. You will be the senior lead, as a team of 1, to develop hybrid, effective, and efficient AML monitoring approaches. The approaches will include, (1) traditional dollar threshold rules based on statistical outlier analysis, (2) targeted rules for high impact scenarios, (3) explainable statistical models, and (4) highly efficient models where effectiveness is the top priority. You will be responsible for performing the research, building the rules/models, and creating master’s thesis level documentation intended to explain the work to produce successful AML Model Validation results and regulatory exam results. This role requires a deep expertise in master's level statistics, an ability to explain the advanced statistics to traditional business and compliance personnel, data programming (SQL and Python preferred), clear plain English writing skills, presentation skills, and the ability to prioritize amongst competing high priorities. This roll will assist with all aspects of Consumer and AML Compliance similar to that of a federally regulated bank, including Anti Money Laundering (“AML”), Customer Identification Program (“CIP”), Consumer Compliance Testing (“CT”), and Distributor Due Diligence (“DDD”).

Requirements

• Graduate Degree, Masters or Ph.D., in Statistics, Math, Engineering, Data Science, Computer Science, or high quantitative discipline.
• 6 years of senior level experience in data science, quantitative analysis, or statistical modeling.
• Professional coding skills, particularly in SQL and Python/R.
• Masters level statistical regression analysis techniques.
• Translation between business/compliance personal to data personnel.
• Educating non math/data personnel on Math and Data concepts.
• Presentation skills to personnel of various backgrounds, math v. non-math, regulatory v. business, etc.
• Ability to work independently and present potential usable end results to Compliance leadership, while being prepared to return for multiple iterative improvements. Especially for feedback from non-math/data professionals.
• Ability to list and prioritize known objectives and workstreams. Especially completing smaller one-off tasks, while keeping the bigger, higher overarching goal projects moving timely.

Nice To Haves

• Master's or Ph.D. in Statistics, Math, or Engineering;
• 6 years of experience in Risk Management Quantitative Field;
• Hands on experience with graphical reporting tools (for example, Tableau, Qlik, Power BI);
• Practical experience with Model Governance and Validation, particularly AML Model Validation and AML Regulatory Exams;
• Prior experience leading or mentoring teams or individuals.

Responsibilities

• Build and utilize statistical feedback loops to periodically tune, calibrate, and optimize AML monitoring rules.
• Build and utilize typologies and AML analyst input to build targeted rules intended for a higher percentage of locating “bad” scenarios.
• Perform and update the Annual AML Risk Assessment based on a calendar year of transactional and account level data (~1 million accounts, ~300+ million transactions).
• Build explainable statistical models with a goal of increasing AML effectiveness. The intended purpose is to use the flagged “bad” accounts from the AML Analyst teams and segment accounts into higher risk buckets in order to improve AML analyst time efficiency by targeting riskier accounts.
• Build effective statistical models using advanced concepts with a focus on effectiveness. This will stand on the foundation of the explainable concepts before it.
• Build professional, master’s level, documentation, to support internal governance, promote understandability, and surpass Model Validation and regulatory benchmarks.
• Build and maintain automated reporting dashboards (using tools like Tableau, Qlik, Pyton, or R) for Monthly, Quarterly, and Annual Oversight Reporting.
• Cross Functional Collaboration: You will partner with different aspects of Compliance, Fraud, and other business departments to translate business, compliance, and regulatory requirements into actionable data driven solutions.
• Communication: You will translate quantitative findings into actionable strategic recommendations for senior leadership and non-math AML Compliance professionals.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior