Job Description :
This Position Is Part Of The Chase 360 Risk Analytics Organization Within Consumer& Community Banking Risk Management. Our Mission Is To Make Better Customer-Level Risk Decisions Through The Use Of Data From Across All Of The Retail And Wholesale Customer Bases Within The Consumer & Community Bank And The Commercial Bank
Description
Customer Risk Data Analysts On The Data Infrastructure & Engineering Team Operate As The Exploratory Group For Locating Valuable Information In Data. They Are Responsible For Identifying Relevant Data Elements That Exist Within And Outside Of Chase, Run Analyses To Transform And Enrich The Data, And Construct The Usable Data Into An Optimally Designed Data Products To Be Loaded Into Our Analytics Environment. They Will Also Be Responsible For Owning The Development And Optimization Of All Customer Analytical Data Products In Our Analytic Environment, Including: Conceptual, Logical, Physical And Semantic Design, Testing, Performance Tuning, Promotion To Production Support Teams, And Ongoing Data Quality Management And Maintenance.
Other Responsibilities Will Include The Following:

Ensure A Robust And Quality Data Environment Is Available To The Ccb Risk Analytics Organization.
Understand How Data Is Created, Transformed, And Used Within And Across Business Processes
Develop Logic For Automated Data Validation
Manage Table And Field Inventory To Risk Requirements, Such As Adding Or Deleting Fields, And Implementing Fixes And Enhancements.

Maintain Documentation
Educational Requirement
Bachelor’S Degree In Related Business, Technical, Or Quantitative Field With 7 Years Of Relevant Experience Or Master’S Degree With 5 Years Of Relevant Experience
Required Skills

Minimum 7 Years Data Management Experience Required, Preferably In A Lending Environment.
Minimum 7 Years’ Experience Required With One Or More Of The Following Applications: Sql Or Similar Data Mining Tools.
Experience With Unix, And At Least One Of: R, Hive, Sparksql, Sqoop, Or Other Query Languages Working With Data In The Hadoop Environment.
Knowledge Of Data Quality Management Is Preferred
Experience In Machine Learning And Ai Is A Plus.
Knowledge Of The Credit Lending Lifecycle, Including Origination, Sale/Servicing, Default Management / Loss Mitigation, Preferred.
Familiarity With Data Warehousing Concepts And Techniques.
Familiarity With Data Governance Principles.
Experience Working In Large-Scale Corporate Data Ecosystems Resolving Inconsistencies And Challenges In The Data
Experience Working With Enterprise Databases Such As Oracle, Db2 And Teradata
Excellent Presentation And Facilitation Skills
Excellent Oral And Written Communication Skills