Applied AI ML Sr Associate

JPMorgan Chase & Co.; Bengaluru; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

JPMorgan Chase & Co. is seeking an Associate in Card Risk Modeling to design and develop an attribute library ensuring data quality across acquisition, management, and transactions.

You will work with senior leadership to deploy innovative machine learning attributes and models into production while monitoring quality and effectiveness of data sources. The role requires deep quantitative expertise, strong communication with senior management, and collaboration across risk, marketing, and

Qualifications

• Master's or PhD in a quantitative field from an accredited university.
• 6+ years of experience with large data and building/implementing attributes and predictive models in credit card domain.
• Proficiency in coding with Python, SAS, Spark, Scala, or TensorFlow; experience with big data platforms.
• Strong knowledge of advanced statistical methods and machine learning techniques (GLM/Regression, Random Forest, Boosting, neural networks, clustering, etc.).
• Ability to understand and interpret data; excellent problem-solving and analytical skills.
• Clear communication with senior management; experience working with US stakeholders is a plus.

Responsibilities

• Design and develop attribute libraries to drive data quality and consistency across customer lifecycle stages.
• Utilize cutting-edge ML approaches to develop attributes and modeling solutions and deploy into production.
• Manage attribute quality testing and monitoring; establish data quality warning systems.
• Evaluate effectiveness of new data sources and data gathering techniques.
• Collaborate with marketing, risk, technology, data governance and control teams through the modeling lifecycle.
• Own data and model quality and ensure compliant development standards and implementations.
• Contribute to knowledge base with innovative approaches to analytic problems and project design.

Skills

Statistical analysis

Machine learning

Data interpretation

Communication with senior management

Stakeholder collaboration

Problem solving

Education

Master’s / PhD in quantitative field

Tools

Python

SAS

Spark

Scala

Tensorflow

Hadoop

HDFS

Teradata

AWS

Hive

Job description

The Data Science and Capability team is a Center of Excellence within CCB Card Modeling focusing on ensuring that the data used in CCB Card models and strategies is of superior quality. The team uses both traditional techniques and advanced techniques like Artificial Intelligence to ensure the same.

Team’s focus is on quality and consistency of existing and new data attributes, developing critical data capability that help derive actionable insight using modern tools and techniques. We are looking for candidates with demonstrated extensive knowledge of data science techniques, strong statistical analysis skills, and expertise in logic and attention to details. In this critical role, the candidate will be responsible for the quality of data and attributes used in Machine Learning Models to safeguard our business and derivation of new information / attributes to identify new opportunities for revenue growth and risk mitigation in card business. The successful candidate must have demonstrated experience working with a wide range of stakeholders and functional teams and be able to effectively communicate results to senior management

Card Risk Modeling -Data Science and CapabilityTeam (Associate)

• Design and development of attribute library to drive consistency and improve quality of data used for machine learning models throughout the customer lifecycle (acquisition, account management, transaction authorization and collection)
• Work closely with the senior management team and utilize cutting-edge machine learning approaches to develop innovative attributes and machine learning modeling solutions, deliver them into production
• Manage attribute quality testing and monitoring by leveraging modern techniques to identify data and attributes issues, patterns, improve attributes accuracy, consistency and establish warning systems / tools
• Evaluate the effectiveness and accuracy of new data sources and data gathering techniques
• Collaborate with various partners in marketing, risk, technology, data governance and control, etc. throughout the entire attributing and modeling lifecycle
• Own quality of attributes and models developed, assuring accurate and appropriate development standards, and right implementation at all times
• Make contributions to the group’s knowledge base by proposing new and creative ways for approaching analytic problems and project design

Basic Qualifications

• Master’s / Phd degree from an accredited university in a quantitative field such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering
• 6 years of experience working with large data, developing or managing the development and implementation of attributes and predictive models in the credit card industry.
• Ability to write high-quality code in traditional as well as modern platforms. At least three years professional experience and proficiency in coding (e.g. Python, SAS, Spark, Scala, or Tensorflow) and big data platform (e.g., Hadoop, HDFS, Teradata, AWS cloud, Hive)
• Solid understanding of advanced statistical methods and advanced machine learning techniques: GLM/Regression, Random Forest, Boosting, Trees, neural networks, clustering, KNN, anomaly detection, simulation, scenario analysis, modeling, etc.
• Strong ability to understand and interpret data
• Advanced problem-solving skills and exceptional analytical skills
• Polished and clear communications with senior management
• Experience working with US stakeholders will be helpful
• Ability to deliver high-quality results under tight deadlines and be comfortable with the manipulation, analysis, and summaraization of large quantities of data.