Consumer & Community Banking - Card Risk Machine Learning - VP at JPMorgan Chase Bank, N.A. (Wilmington, DE)

JPMorgan Chase & Co . (NYSE: JPM) is a leading global financial services firm with operations worldwide. The Firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of customers in the United States and many of the world's most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com

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 Data Center of Excellence within CCB Card Modeling. Data is the lifeblood of Machine Learning. We focus on driving quality and consistency of existing and new data and attributes, driving critical data capability and deriving 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
* Lead the design and develop data quality control procedures to enhance the accuracy and integrity of modeling data throughout the customer lifecycle (e.g., acquisition, account management, transaction authorization, collection)
* Manage data quality testing by leveraging modern techniques to identify data issues, improve data accuracy, consistency and efficiency
* Lead the development of processes and tools to monitor data accuracy and model performance
* Assess the effectiveness and accuracy of new data sources and data gathering techniques
* 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
* Collaborate with various partners in marketing, risk, technology, model governance, etc. throughout the entire attributing and modeling lifecycle (existing attribute correction and improvement, new attribute and model development, review, deployment, and usage)

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
* At least eight years of experience working with large data, developing or managing the development and implementation of predictive models in the credit card industry
* Ability to write high-quality code. At least five 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

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.

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.

Equal Opportunity Employer/Disability/Veterans

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