Applied AI ML Associate

We offer an exciting opportunity to advance your quantitative modeling career in a team that values creativity and excellence.

As an Applied AI ML Associate in the Data Analytics team, you will design and develop statistical and machine learning models that drive informed decision-making across the firm. You will collaborate with diverse teams and contribute to impactful solutions supporting business objectives.

Job responsibilities

• Identify data anomalies and investigate issues during model development
• Perform advanced quantitative and statistical analysis of large datasets to uncover trends and patterns
• Clean and prepare modeling datasets for analysis
• Build statistical and econometric models for budgeting, financial analysis, and regulatory requirements
• Develop machine learning models for optimal pricing decisions across Deposits, Auto, Home Lending, and Cards products
• Communicate modeling results to Finance partners, Risk teams, and Model Governance
• Mentor team members in model development and statistical analysis

Required qualifications, capabilities, and skills

• Graduate degree (M.S. or Ph.D.) in Statistics, Economics, Mathematics, Operations Research, Engineering, or Computer Science
• Five years of hands-on model development experience
• Strong programming skills in Python or PySpark
• Proficient in statistics, econometric modeling, and time series analysis
• Experience with linear and non-linear modeling, panel data analysis, Bayesian and non-parametric methods
• Solid foundation in machine learning theory and end-to-end development
• Experience in big data processing with Spark or Hadoop and Unix operating systems

Preferred qualifications, capabilities, and skills

• Hands-on experience in budget and regulatory (CCAR) modeling for Deposits, Wealth Management, or lending products
• Expertise in Python familiarity with PySpark, TensorFlow, and Gen AI applications
• knowledge of TensorFlow is an advantage
• Experience hosting and maintaining machine learning applications knowledge of container services is a plus