Ai-ml Modeler - Senior Associate

JPMorgan Chase · Banking · Bengaluru, Karnataka, India · Consumer & Community Banking

Senior Associate AI-ML Modeler at JPMorgan Chase in Bengaluru, India, focusing on designing and delivering innovative models for budgeting, financial analysis, regulatory requirements, and pricing decisions. The role involves advanced quantitative analysis, data cleaning, model building using statistical, econometric, and machine learning techniques, and communicating results to stakeholders. Requires a graduate degree, 5+ years of model development experience, proficiency in Python/R/Scala, experience with big data tools, and understanding of ML explainability for risk and compliance.

What you'd actually do

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

Skills

Required

Graduate degree (M.S. or Ph.D.) in Statistics, Economics, Mathematics, Operations Research, Engineering, or Computer Science
5 + years of model development
Proficient in Python or R or Scala
Experience developing budget, regulatory (CCAR), and PPNR models
Experience with statistical and econometric modeling techniques
Strong foundation in machine learning theory and end-to-end development
Proficient in big data processing tools such as Spark or Hadoop
Unix operating systems
Ability to communicate complex concepts effectively with non-technical stakeholders
Proven ability to create price elasticity models
implement scalable machine learning and big data frameworks
Deep understanding of machine learning explainability

Nice to have

Hands-on experience in budget and regulatory (CCAR) modeling for Deposit/Wealth Management or lending products
Experience with machine learning models
familiarity with Gen AI applications
Expertise in Python
knowledge of PySpark or TensorFlow
Excellent written and oral communication and presentation skills
Scalable Machine Learning / Big data framework

What the JD emphasized

regulatory requirements
regulatory (CCAR)
machine learning explainability
risk control
regulatory compliance

Other signals

model development
advanced analytics
regulatory requirements
machine learning theory
end-to-end development
machine learning explainability
risk control
regulatory compliance

Read full job description

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

We have an exciting and rewarding opportunity for you to advance your AI-ML modeling career in our Finance Modeling team.

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