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Quantitative Analytics & Model Development Analyst - Balance Sheet Analytics & Modeling

LinkedIn PNC Philadelphia, PA
Not Applicable Posted April 2, 2026 2 variants Job link
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Requirements
  • Experience in developing GenAI solutions
  • Experience with data mining, and data preparation for ML models including EDA, data transformations and preprocessing
  • 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
  • Familiarity with big data technologies like Hadoop, Spark, Hive, Impala etc.
  • 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
  • Analytical Thinking, Credit Risks, Data Analytics, Financial Analysis, Model Development, Operational Risks, Quantitative Models, Risk Appetite
  • Bank Quantitative Analysis, Consulting, Data Gathering and Reporting, Effective Communications, Predictive Analytics, Quantitative Techniques, Regulatory Environment - Financial Services, Testing
  • Roles at this level typically require a university / college degree, with 3+ years of relevant / direct industry experience.
  • No Required Certification(s)
Preferred Skills
  • Experience with data mining, and data preparation for ML models including EDA, data transformations and preprocessing
  • Expertise in building, scaling, and optimizing machine learning systems with industry recognized ML frameworks and algorithms
  • Familiarity with big data technologies like Hadoop, Spark, Hive, Impala etc.
  • 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
  • Master’s degree in Statistics or Econometrics
  • 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
  • Analytical Thinking, Credit Risks, Data Analytics, Financial Analysis, Model Development, Operational Risks, Quantitative Models, Risk Appetite
  • Bank Quantitative Analysis, Consulting, Data Gathering and Reporting, Effective Communications, Predictive Analytics, Quantitative Techniques, Regulatory Environment - Financial Services, Testing
  • Certifications are often desired.
Education
  • (Not required) – Master's degree or higher in a quantitative field
  • (Not required) – Master’s degree in Statistics or Econometrics
  • (Not required) – Roles at this level typically require a university / college degree, with 3+ years of relevant / direct industry experience.
  • (Not required) – Certifications are often desired.
  • (Not required) – In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.
  • (Not required) – Education
  • (Not required) – Bachelors
  • (Required) – No Required Certification(s)