Fraud Model Analyst at PNC supporting data-driven fraud detection through advanced analytics. Collaborating across teams to optimize business outcomes using machine learning and statistical modeling techniques.
Responsibilities
Supports the team with 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
Supports the team in developing algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes
Assists with 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
Requirements
Python
R Language
SQL
SAS
Statistical Modeling (nice to have)
Validation
Data Science
Statistics and Data Analytics
Graph Database experience
Data Correlation and Visualization
2+ years of relevant professional experience
Bachelor's degree
Benefits
medical/prescription drug coverage (with a Health Savings Account feature)
dental and vision options
employee and spouse/child life insurance
short and long-term disability protection
401(k) with PNC match
pension and stock purchase plans
dependent care reimbursement account
back-up child/elder care
adoption, surrogacy, and doula reimbursement
educational assistance, including select programs fully paid
a robust wellness program with financial incentives
maternity and/or parental leave
up to 11 paid holidays each year
9 occasional absence days each year, unless otherwise required by law
between 15 to 25 vacation days each year, depending on career level; and years of service
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