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Cons Prod Strategic Analyst III-Pre Paid Unemployment

Newark, Delaware;

Job Description:

Line of Business Role Description

The GBAM Fraud Strategies & Analytics Team is looking for an experienced analytical professional to join our team supporting Prepaid Card Fraud Strategies. In this role, you will be expected to quantify/assess fraud risks associated with the Prepaid Card product, partnering with Product, Data Technology teams, GIS/GFC, Model Development & Governance, Vendors (Visa) and Fraud & Claims Operations management. The incumbent will assist with developing business cases to enhance/create fraud rules, defining business requirements for fraud initiatives and utilizing knowledge of Identity Fraud, Malware, Phishing, Business Email Compromise, Account Takeover and other fraud risks to best mitigate 1st and 3rd party fraud balancing the customer experience with appropriate controls.

Development of new fraud strategies using statistical and analytical techniques and other quantitative methods. Goal will be to identify and mitigate new and emerging fraud threats.
Identifying new sources of data (internal or vendor-provided) that can enrich our existing fraud detection processes, be added to our decision systems, and allow for new detection strategies to be developed. Will require close coordination with partners in Fraud Technology.
Leading role managing projects related to technology initiatives including decision engine enhancements and authentication tool deployment. 
Optimization of existing detection strategies to determine areas where rules can be adjusted to decline fewer false positives and improve the ROI and overall performance of our fraud strategies
Development of both ad-hoc and more standardized reporting (MIS)
 Liaise with internal and external partners on fraud trends.
Represent the business on matters pertaining to Fraud Strategies"

Required skills

The candidate must be at an advanced to expert level in SAS and SQL.  Familiarity with other programming languages and knowledge of data extraction tools will be useful.

Fraud decision engine management experience highly preferred.
Experience working in analytical environment with a strong preference towards prior financial services or cyber security roles.
Proven track record in Logic and critical thinking to identify trends and make data-driven recommendations.
Ability to work in a fast-paced, dynamic environment is critical. 
Advanced degree, preferably in a quantitative discipline such as mathematics, statistics, operations research, engineering, computer science, finance or business is preferred.

 Commercial Pre-Paid Card knowledge a plus.

Strives to bring new thoughts and ideas; ability to evidence critical thinking skills.

Is able to consider diverse viewpoints to determine the best path forward.
Commitment to challenging the status quo and promoting positive change.
Participates in and drives collaborative efforts to advance tools, technology and ways of working to better serve an evolving fraud landscape.

Job Band:

H5

Shift: 

1st shift (United States of America)

Hours Per Week:

40

Weekly Schedule:

Referral Bonus Amount:

0

Job Description:

Line of Business Role Description

The GBAM Fraud Strategies & Analytics Team is looking for an experienced analytical professional to join our team supporting Prepaid Card Fraud Strategies. In this role, you will be expected to quantify/assess fraud risks associated with the Prepaid Card product, partnering with Product, Data Technology teams, GIS/GFC, Model Development & Governance, Vendors (Visa) and Fraud & Claims Operations management. The incumbent will assist with developing business cases to enhance/create fraud rules, defining business requirements for fraud initiatives and utilizing knowledge of Identity Fraud, Malware, Phishing, Business Email Compromise, Account Takeover and other fraud risks to best mitigate 1st and 3rd party fraud balancing the customer experience with appropriate controls.

Development of new fraud strategies using statistical and analytical techniques and other quantitative methods. Goal will be to identify and mitigate new and emerging fraud threats.
Identifying new sources of data (internal or vendor-provided) that can enrich our existing fraud detection processes, be added to our decision systems, and allow for new detection strategies to be developed. Will require close coordination with partners in Fraud Technology.
Leading role managing projects related to technology initiatives including decision engine enhancements and authentication tool deployment. 
Optimization of existing detection strategies to determine areas where rules can be adjusted to decline fewer false positives and improve the ROI and overall performance of our fraud strategies
Development of both ad-hoc and more standardized reporting (MIS)
 Liaise with internal and external partners on fraud trends.
Represent the business on matters pertaining to Fraud Strategies"

Required skills

The candidate must be at an advanced to expert level in SAS and SQL.  Familiarity with other programming languages and knowledge of data extraction tools will be useful.

Fraud decision engine management experience highly preferred.
Experience working in analytical environment with a strong preference towards prior financial services or cyber security roles.
Proven track record in Logic and critical thinking to identify trends and make data-driven recommendations.
Ability to work in a fast-paced, dynamic environment is critical. 
Advanced degree, preferably in a quantitative discipline such as mathematics, statistics, operations research, engineering, computer science, finance or business is preferred.

 Commercial Pre-Paid Card knowledge a plus.

Strives to bring new thoughts and ideas; ability to evidence critical thinking skills.

Is able to consider diverse viewpoints to determine the best path forward.
Commitment to challenging the status quo and promoting positive change.
Participates in and drives collaborative efforts to advance tools, technology and ways of working to better serve an evolving fraud landscape.

Shift:

1st shift (United States of America)

Hours Per Week: 

40

Learn more about this role

Full time

JR-21083306

Band: H5

Manages People: No

Travel: Yes, 5% of the time

Manager:

Talent Acquisition Contact:

Larisa McLaughlin

Referral Bonus:

0