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Applied AI ML Lead

ExperiencedNo visa sponsorship
J.P. Morgan logo

at J.P. Morgan

Bulge Bracket Investment Banks

Posted 5 days ago

No clicks

**Applied AI ML Lead - Bengaluru, India** Guide & build AI-ML models for banking decisions. Design & manage teams of 10+ yrs exp. Specialists in Python, PySpark, machine learning. MS/PhD required. Collaborate cross-functionally, communicate results effectively.

Compensation
Not specified

Currency: Not specified

City
Bengaluru
Country
India

Full Job Description

Location: Bengaluru, Karnataka, India

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 Lead 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 firms success through advanced analytics and model development.

 

Job Responsibilities

  • Perform advanced quantitative and statistical analysis of large datasets to uncover trends and insights 
  • 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
  • Experience in leading & managing teams to deliver best in class statistical, econometric & ML models

     

 

Required qualifications, capabilities, and skills

  • Graduate degree (M.S. or Ph.D.) in Statistics, Economics, Mathematics, Operations Research, Engineering, or Computer Science
  • 10+ years of hands-on model development experience
  • Proficient in Python & PySpark with strong programming and development skills
  • 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
  • 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
  • Experience in leading & managing high performance teams to deliver statistical, econometric, or machine learning models 

 

Preferred qualifications, capabilities, and skills

  • Hands-on experience in budget and regulatory (CCAR) modeling for deposit growth, fee revenue, or other business drivers
  • Knowledge of components of PPNR models for deposit & wealth management portfolio
  • Understanding forecasting the performance of branches or bankers, in order to optimize the branch network and staffing
  • Creating price elasticity models to optimize deposit and loan (Auto, Home Lending & Cards) pricing
  • Model-based automatic machine learning
  • Machine Learning Explainability for risk control
  • Scalable Machine Learning / Big data framework
Develop AI-ML models to drive impactful financial solutions at a leading global bank.

Applied AI ML Lead

Compensation

Not specified

City: Bengaluru

Country: India

J.P. Morgan logo
Bulge Bracket Investment Banks

5 days ago

No clicks

at J.P. Morgan

ExperiencedNo visa sponsorship

**Applied AI ML Lead - Bengaluru, India** Guide & build AI-ML models for banking decisions. Design & manage teams of 10+ yrs exp. Specialists in Python, PySpark, machine learning. MS/PhD required. Collaborate cross-functionally, communicate results effectively.

Full Job Description

Location: Bengaluru, Karnataka, India

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 Lead 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 firms success through advanced analytics and model development.

 

Job Responsibilities

  • Perform advanced quantitative and statistical analysis of large datasets to uncover trends and insights 
  • 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
  • Experience in leading & managing teams to deliver best in class statistical, econometric & ML models

     

 

Required qualifications, capabilities, and skills

  • Graduate degree (M.S. or Ph.D.) in Statistics, Economics, Mathematics, Operations Research, Engineering, or Computer Science
  • 10+ years of hands-on model development experience
  • Proficient in Python & PySpark with strong programming and development skills
  • 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
  • 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
  • Experience in leading & managing high performance teams to deliver statistical, econometric, or machine learning models 

 

Preferred qualifications, capabilities, and skills

  • Hands-on experience in budget and regulatory (CCAR) modeling for deposit growth, fee revenue, or other business drivers
  • Knowledge of components of PPNR models for deposit & wealth management portfolio
  • Understanding forecasting the performance of branches or bankers, in order to optimize the branch network and staffing
  • Creating price elasticity models to optimize deposit and loan (Auto, Home Lending & Cards) pricing
  • Model-based automatic machine learning
  • Machine Learning Explainability for risk control
  • Scalable Machine Learning / Big data framework
Develop AI-ML models to drive impactful financial solutions at a leading global bank.