Independently performs advanced quantitative analyses and model development to drive decision-making by running quantitative strategies
Makes recommendations based on analyses
Analyzes and develops new model frameworks by supporting the line of business
Refines, monitors, and reviews existing models
Conducts on-going communication with model owners and model developers during the course of the review
Works with larger, more complex datasets to create models
Performs quantitative analysis and develops complex reports
Performs qualitative and quantitative assessments of all aspects of models including theoretical aspects, model design and implementation as well as data quality and integrity
Analyzes complex data and associated quantitative analysis
Makes recommendations based on findings from data analytics
Uses quantitative tools and techniques to measure and analyze model risks and reaches conclusions on strengths and limitations of the model
Prepares and analyzes detailed documents for validation and regulatory compliance, using applicable templates
Requirements
Master's degree or higher in a quantitative field
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
Master’s degree in Statistics or Econometrics (preferred)
Experience in banking/ financial services (preferred)
Experience with anti-fraud and/or anti-money laundering modeling (preferred)
Hands-on experience building various types of AI/ML models, including neural networks (preferred)
Experience with cloud platforms like AWS, Google Cloud, or Azure (preferred)
Tech Stack
AWS
Azure
Cloud
Hadoop
PySpark
Python
Spark
SQL
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