Description
:
This job is responsible for performing more complex analysis and modeling to minimize loss exposure and negative impacts to the customer experience. Key responsibilities include utilizing a variety of systems such as Excel, SAS, SQL, Tableau, and other relational data bases to provide analytical support on strategies, ensure goals are met, and propose policy and procedural changes within segmentation structures to produce optimal results. Job expectations include evaluating data to assess potential fraud risk and create mitigation strategies.
Responsibilities:
1. Recommends ways to help the business achieve desired outcomes and make informed business decisions using data analysis outputs
2. Performs complex analysis of financial models, market data, financial data, and portfolio trends to understand product performance and improve portfolio risk, profitability, performance forecasting, and operational performance
3. Leads coordination of the production of product performance reports and updates for senior management
Skills:
4. Business Analytics
5. Business Intelligence
6. Data Quality Management
7. Fraud Management
8. Monitoring, Surveillance, and Testing
9. Collaboration
10. Data Visualization
11. Oral Communications
12. Problem Solving
13. Written Communications
14. Analytical Thinking
15. Critical Thinking
16. Data and Trend Analysis
17. Innovative Thinking
18. Research
LOB Specific Information:
The Client Protection data analyst will provide analytical and data support for Consumer fraud and non-fraud products supporting adhoc report and analytical requests to support fraud and claims LOBs. The candidate will coordinate the production of performance reports and updates for key stakeholders in strategy, claims, finance, and product. The candidate will utilize established databases to provide performance insights to key stakeholders. The candidate will be tasked with analyzing and completing adhoc reports that will provide insights into performance, risk, client impacts, recoveries, and potential gaps. SAS/SQL technical skills required. Good working experience with Tableau, HIVE SQL, and Python is a plus.
19. Analyze complex data to provide insights into incoming and loss trends or identify potential problems
20. Develop reporting for Consumer Card Products and Channels including audit / regulatory reports
21. Identify process improvements and efficiencies via data analysis
22. Participate in collaborative reporting and design sessions with organizational stakeholders and business owners to design, build, and deliver reports and dashboards to meet business goal
23. Develop and maintain automated production environment using stored procedures
24. Collaborate with other developers to create / maintain scalable processes and best practices
25. Manage multiple projects, shifting priorities as needed to produce accurate work while meeting established deadlines
26. Deliver accurate metrics related to fraud and claim activity
27. Validate the integrity and quality of data required for performing analysis
28. Partner with claims, policy, strategy, and product teams to deliver data insights and analysis that inform critical decisions and help achieve goals.
29. Other duties as assigned
Required Qualifications:
30. 3+ years of fraud experience and/or 3+ years of analytical experience (Payment card /Retail Bank background preferred)
31. 3+ years of SAS and / or SQL .
32. 3+ years of Tableau or Microstrategy
33. Strong quantitative, critical thinking, and analytical skills
34. Ability to communicate and interact with a high degree of professionalism with executive level personnel across the business
35. Ability to work independently as well as part of a virtual team
36. Innovative mindset with the ability to challenge the status quo
37. Ability to proactively identify, analyze, and improve upon existing processes for optimization and to meet deadlines
38. Proven strong analytical and communication skills
39. This position is not eligible for sponsorship
Desired Qualifications:
40. Bachelors degree in a quantitative discipline such as mathematics, statistics, operations research, finance, or business
41. Advanced analytical and quantitative skills with demonstrated ability in using data and metrics to identify root causes
42. Basic understanding of 1st and 3rd party fraud (claims to charge-off timing, chargeback recovery rights, etc.)
43. Python, Hadoop
Shift:
1st shift (United States of America)
Hours Per Week:
40