We have an exciting and rewarding opportunity for you to advance your AI-ML modeling career in our Finance Modeling team.
As an AI-ML Modeler in the Finance Modeling team, you design and deliver innovative models that support informed decision-making and business growth. You collaborate with diverse teams and contribute to the firm's success through advanced analytics and model development.
Job Responsibilities
Identify data anomalies and cases requiring further investigation during model development
Perform advanced quantitative and statistical analysis of large datasets to uncover trends and insights
- Prepare and clean modeling datasets for analysis
- Build statistical, econometric, or machine learning models for budgeting, financial analysis, regulatory requirements, and pricing decisions
- Communicate analytical results to Finance partners, modeling teams, and Model Governance
Mentor team members in model development and effective communication of results
Required qualifications, capabilities, and skills
- Graduate degree (M.S. or Ph.D.) in Statistics, Economics, Mathematics, Operations Research, Engineering, or Computer Science
- Hands-on experience of 5 + years of model development
- Proficient in Python or R or Scala, with strong programming and development skills
- Experience developing budget, regulatory (CCAR), and PPNR models for deposit growth, fee revenue, and wealth management portfolios
- Experience with statistical and econometric modeling techniques, including time series, panel data, Bayesian, and non-parametric methods
- Strong foundation in machine learning theory and end-to-end development, including NLP, computer vision, or reinforcement learning
- Proficient in big data processing tools such as Spark or Hadoop and Unix operating systems
- Ability to communicate complex concepts effectively with non-technical stakeholders
- Proven ability to create price elasticity models for deposit and loan products (Auto, Home Lending, Cards), and implement scalable machine learning and big data frameworks, including model-based automatic machine learning.
- Deep understanding of machine learning explainability to support risk control and regulatory compliance, promoting transparency and robust risk management.
Preferred qualifications, capabilities, and skills
- Hands-on experience in budget and regulatory (CCAR) modeling for Deposit/Wealth Management or lending products
- Experience with machine learning models and familiarity with Gen AI applications
- Expertise in Python, with knowledge of PySpark or TensorFlow
- Excellent written and oral communication and presentation skills
- Scalable Machine Learning / Big data framework
