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
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 summarization of large quantities of data.
Job description provided by JPMorgan Chase.
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