Data Scientist - Anti-Money Laundering Analytics & Modeling

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

Position Overview

At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company's success. As a Data Scientist within PNC's Anti-Money Laundering Analytics & Modeling organization, you will be based in Pittsburgh, or Philadelphia, PA; Wilmington, DE, Cleveland, OH; Charlotte, NC; Austin, TX; or Washington, DC.

Job Summary:

As a Data Scientist within PNC's Anti-Money Laundering Analytics & Modeling team, you will be part of a cohesive team of professionals who utilize a variety of statistical techniques to build models to detect, monitor, and avert concerning patterns of account activity. In this role, you will work with key stakeholders across the bank to identify patterns and risk indicators within the firm's account and transaction datasets, identify opportunities for new strategies, and recommend improvements to existing strategies.

You will be leading innovative AML projects that are patentable, utilizing statistical techniques, including logistic regression, clustering, gradient boosting, neural network, and other machine learning algorithms, to design samples and build statistical models.

Specific responsibilities for this role include (but are not limited to):

• Use a variety of analytical techniques to extract usable information from various data sources, including customer, account, and transactional data sets
• Participate in data set creation, analysis, reporting, model building, model monitoring and model documentation
• Effectively communicate analytical results, represent the modeling team in various forums to inform senior executives and various team partners of progress on key modeling efforts
• Collaboration with 1st, 2nd and 3rd line of defenses and other key stakeholders

Preferred experience/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

Additional preferred qualifications:

• Experience in banking/ financial services
• Experience with anti-fraud and/or anti-money laundering modeling
• Hands-on experience building various types of AI/ML models, including neural networks
• Experience with cloud platforms like AWS, Google Cloud, or Azure

PNC is an in-office company that fosters a supportive culture where employees can thrive and achieve balance. We encourage candidates to connect with their recruiter and hiring manager to understand workplace expectations and ensure the role aligns with their goals.

PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position.

Job Description

Performs analytical tasks on vast amounts of structured and unstructured data to extract actionable business insights.

Participates in the data gathering, data processing and data mining of large and complex datasets.

Develops algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management.

Runs analytical experiments in a methodical manner to find opportunities for product and process optimization. Assists in the presentation of business insights to management using visualization technologies and data storytelling.

May partner with Data Architects, Data Analysts, Data Engineers and Visualization Experts to develop data-driven solutions for the business.

PNC Employees take pride in our reputation and to continue building upon that we expect our employees to be:

• Customer Focused - Knowledgeable of the values and practices that align customer needs and satisfaction as primary considerations in all business decisions and able to leverage that information in creating customized customer solutions.
• Managing Risk - Assessing and effectively managing all of the risks associated with their business objectives and activities to ensure they adhere to and support PNC's Enterprise Risk Management Framework.

Qualifications

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