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Senior Associate - Quant Modeling

ExperiencedNo visa sponsorship
J.P. Morgan logo

at J.P. Morgan

Bulge Bracket Investment Banks

Posted 15 days ago

No clicks

**Senior Associate - Quant Modeling (Mumbai, India)** - Senior Associate designs and implements portfolio risk models for consumer banking. - Applies advanced statistical techniques (logistic/multinomial regression, multivariate analysis, etc.) for risk calculation, forecasting, and monitoring. - Develops, tests, validates, and documents models, ensuring quality and repeatability using R, Python, PySpark, and AWS. - Collaborates with stakeholders, managing expectations and delivering high-quality results. - 5+ years of financial services industry experience, Master's/Ph.D. in a quantitative field; proficiency in advanced analytical languages essential.

Compensation
Not specified

Currency: Not specified

City
Mumbai
Country
India

Full Job Description

Location: Mumbai, Maharashtra, India

Our Firmwide Risk Function is focused on cultivating a stronger, unified culture that embraces a sense of personal accountability for developing the highest corporate standards in governance and controls across the firm. Business priorities are built around the need to strengthen and guard the firm from the many risks we face, financial rigor, risk discipline, fostering a transparent culture and doing the right thing in every situation. We are equally focused on nurturing talent, respecting the diverse experiences that our team of Risk professionals bring and embracing an inclusive environment.

Job summary

As a Portfolio Risk Modeling Senior Associate within Consumer & Community Banking Risk Management, you will support critical statistical development projects and related analysis. You will design, develop, test, and validate statistical models for risk weight calculation, risk forecasting, and model performance monitoring. You will apply graduate-level research and analytical skills to perform data extraction, sampling, and statistical analyses using methods such as logistic regression, multinomial regression, multivariate analysis, discriminant analysis, time series analysis, and panel data analysis. You will design and produce programs to streamline and create repeatable procedures for model development, validation, and reporting. You will communicate and collaborate with business partners and model end-users to analyze and meet analysis and reporting needs.

Job responsibilities

  • Design statistical models for risk weight calculation, risk forecasting, and model performance monitoring.
  • Develop statistical models and related analytics to support critical development projects.
  • Test models and supporting code to ensure accuracy and stability.
  • Validate models and monitoring approaches, including documenting model performance.
  • Perform data extraction, sampling, and statistical analyses using techniques such as logistic regression, multinomial regression, multivariate analysis, discriminant analysis, time series analysis, and panel data analysis.
  • Build efficient programs to streamline and create repeatable procedures for model development, validation, and reporting.
  • Communicate proactively with business partners and model end-users on analysis objectives, progress, and results.
  • Collaborate with partners and end-users to define and meet analysis and reporting needs.

Required qualifications, capabilities, and skills

  • Qualified graduate with minimum of 5 years of relevant experience in statistical modeling within financial services industry
  • Proficiency in advanced analytical languages such as R, Python, PySpark, and AWS
  • Masters or Ph.D. degree in a technical or quantitative field such as Statistics, Economics, Finance, Mathematics, Computer Science, Engineering, or Information Technology
  • Strong analytical and problem-solving skills
  • Strong organization and time management skills, with the ability to deliver high-quality results under tight deadlines
  • Strong multi-tasking skills, with demonstrated ability to manage expectations and deliver results
  • Strong communication skills

Preferred qualifications, capabilities, and skills

  • Knowledge of regulatory modeling (IFRS 9 / CECL / CCAR / Basel)

 

Build and validate portfolio risk models that forecast performance and strengthen governance across consumer banking.

Senior Associate - Quant Modeling

Compensation

Not specified

City: Mumbai

Country: India

J.P. Morgan logo
Bulge Bracket Investment Banks

15 days ago

No clicks

at J.P. Morgan

ExperiencedNo visa sponsorship

**Senior Associate - Quant Modeling (Mumbai, India)** - Senior Associate designs and implements portfolio risk models for consumer banking. - Applies advanced statistical techniques (logistic/multinomial regression, multivariate analysis, etc.) for risk calculation, forecasting, and monitoring. - Develops, tests, validates, and documents models, ensuring quality and repeatability using R, Python, PySpark, and AWS. - Collaborates with stakeholders, managing expectations and delivering high-quality results. - 5+ years of financial services industry experience, Master's/Ph.D. in a quantitative field; proficiency in advanced analytical languages essential.

Full Job Description

Location: Mumbai, Maharashtra, India

Our Firmwide Risk Function is focused on cultivating a stronger, unified culture that embraces a sense of personal accountability for developing the highest corporate standards in governance and controls across the firm. Business priorities are built around the need to strengthen and guard the firm from the many risks we face, financial rigor, risk discipline, fostering a transparent culture and doing the right thing in every situation. We are equally focused on nurturing talent, respecting the diverse experiences that our team of Risk professionals bring and embracing an inclusive environment.

Job summary

As a Portfolio Risk Modeling Senior Associate within Consumer & Community Banking Risk Management, you will support critical statistical development projects and related analysis. You will design, develop, test, and validate statistical models for risk weight calculation, risk forecasting, and model performance monitoring. You will apply graduate-level research and analytical skills to perform data extraction, sampling, and statistical analyses using methods such as logistic regression, multinomial regression, multivariate analysis, discriminant analysis, time series analysis, and panel data analysis. You will design and produce programs to streamline and create repeatable procedures for model development, validation, and reporting. You will communicate and collaborate with business partners and model end-users to analyze and meet analysis and reporting needs.

Job responsibilities

  • Design statistical models for risk weight calculation, risk forecasting, and model performance monitoring.
  • Develop statistical models and related analytics to support critical development projects.
  • Test models and supporting code to ensure accuracy and stability.
  • Validate models and monitoring approaches, including documenting model performance.
  • Perform data extraction, sampling, and statistical analyses using techniques such as logistic regression, multinomial regression, multivariate analysis, discriminant analysis, time series analysis, and panel data analysis.
  • Build efficient programs to streamline and create repeatable procedures for model development, validation, and reporting.
  • Communicate proactively with business partners and model end-users on analysis objectives, progress, and results.
  • Collaborate with partners and end-users to define and meet analysis and reporting needs.

Required qualifications, capabilities, and skills

  • Qualified graduate with minimum of 5 years of relevant experience in statistical modeling within financial services industry
  • Proficiency in advanced analytical languages such as R, Python, PySpark, and AWS
  • Masters or Ph.D. degree in a technical or quantitative field such as Statistics, Economics, Finance, Mathematics, Computer Science, Engineering, or Information Technology
  • Strong analytical and problem-solving skills
  • Strong organization and time management skills, with the ability to deliver high-quality results under tight deadlines
  • Strong multi-tasking skills, with demonstrated ability to manage expectations and deliver results
  • Strong communication skills

Preferred qualifications, capabilities, and skills

  • Knowledge of regulatory modeling (IFRS 9 / CECL / CCAR / Basel)

 

Build and validate portfolio risk models that forecast performance and strengthen governance across consumer banking.