AML Analytics & Modeling Data Scientist

PNC; Pittsburgh (Allegheny County); On-site; USD 120,000 - 180,000; Full time

Job summary

PNC is seeking a Data Scientist for its Anti-Money Laundering Analytics & Modeling team. Based in multiple U.S. cities, you will build models to detect suspicious activity and advise stakeholders across the bank on risk indicators and strategies.

You will lead ML-driven AML projects, employing logistic regression, clustering, gradient boosting, neural networks, and related techniques to develop scalable models and monitoring processes.

Qualifications

• Master's degree or higher in a quantitative field.
• Experience with data mining and data preparation for ML models.
• Proficiency in statistical methods and tools, including experimental design, probability theory, and sampling.
• Expertise in building, scaling, and optimizing machine learning systems with industry recognized ML frameworks and algorithms.
• Strong programming skills in Python, PySpark, R, and/or SQL.
• Experience working with model risk governing bodies in model validation, and with model implementation partners in productionizing a model.
• Critical thinking and problem-solving aptitude with the ability to apply analytical rigor to complex business problems.
• Ability to present complex technical concepts clearly and effectively to non-technical stakeholders and business partners.
• Ability to manage multiple projects simultaneously.
• Strong teamwork skills and ability to work across different departments.
• Experience in banking/ financial services; anti-fraud/AML modeling and cloud platforms.

Responsibilities

• Use a variety of analytical techniques to extract usable information from customer, account, and transactional data sets.
• Participate in data set creation, analysis, reporting, model building, model monitoring and model documentation.
• Effectively communicate analytical results and inform senior executives and partners of progress on key modeling efforts.
• Collaboration with 1st, 2nd and 3rd line of defenses and other key stakeholders.
• Lead innovative AML projects that are patentable and leverage ML algorithms to design samples and build models.

Skills

Python

PySpark

R

SQL

Machine Learning

Statistical Methods

Experiment Design

Communication

Project Management

Cloud Platforms

Education

Master's degree in quantitative field

Tools

AWS

Google Cloud

Azure

ML Frameworks

Job description

PNC is seeking a Data Scientist for its Anti-Money Laundering Analytics & Modeling team. Based in multiple U.S. cities, you will build models to detect suspicious activity and advise stakeholders across the bank on risk indicators and strategies.

You will lead ML-driven AML projects, employing logistic regression, clustering, gradient boosting, neural networks, and related techniques to develop scalable models and monitoring processes.