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PNC Financial Services GroupPosted 1 month ago

Data Scientist - Enterprise Fraud Organization

$86,250–$172,500 year

On-sitePittsburgh, Pennsylvania, United States or Birmingham, Alabama, United States

Full TimeDoctorate Or Professional DegreeEnterprise

Job Summary

Develop effective anomaly detection metrics and monitoring tools to identify potential fraud by analyzing data to detect suspicious activity and surface emerging trends. Partner with cross-functional teams to share insights and continuously improve fraud mitigation processes through the development of algorithms using machine learning to predict business outcomes. Present actionable business insights to management using visualization technologies and data storytelling while assisting in the presentation of findings. Conduct analytical experiments in a methodical manner to find opportunities for product and process optimization within the React Identify team.

Required Qualifications

  • university / college degree
  • 3+ years of relevant / direct industry experience
  • Master's Certifications
  • Data Science
  • Machine Learning (ML)
  • Data Architecture
  • Data Mining
  • Modeling: Data, Process, Events, Objects, Prototyping, Query and Database Access Tools
  • Order to Cash
  • Procure to Pay
  • Supply Chain
  • Customers
  • Suppliers
  • Risk Identification
  • Business Acumen
  • Time Management
  • Stakeholder Management
  • analytical tasks on vast amounts of structured and unstructured data
  • data gathering, data processing and data mining of large and complex datasets
  • algorithms using advanced mathematical and statistical techniques like machine learning
  • visualization technologies and data storytelling
  • Pittsburgh, PA, Cleveland, OH, Dallas, TX, or Birmingham, AL

Desired Qualifications

  • Certifications are often desired
  • In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered
  • Analytical Thinking
  • Competitive Advantages
  • Data Analytics
  • Data Mining
  • Data Science
  • Machine Learning (ML)
  • Disruptive Innovation
  • Information Capture
  • Modeling: Data, Process, Events, Objects, Prototyping, Query and Database Access Tools

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