JPMorgan Chase Bank, N.A. | Hiring | CCB Risk – Machine Learning Modeling – Associate | Bangalore | BigDataKB.com | 2022-09-28

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.

Chase Consumer & Community Banking (CCB) serves consumers and small businesses with a broad range of financial services, including personal banking, small business banking and lending, mortgages, credit cards, payments, auto finance and investment advice. Consumer & Community Banking Risk Management partners with each CCB sub-line of business to identify, assess, prioritize and remediate risk. Chase Card Services is the top issuer of US credit cards.

The Data Science and Capability team isa 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 Capability Team (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

• Ph.D. or Master’s degree from an accredited university in a quantitative field such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering
• 3 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 summarization of large quantities of data.

JPMorgan Chase & Co., one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. In accordance with applicable law, we make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as any mental health or physical disability needs.