Forensics – Anti Fraud Data Analyst – Deals

Job Description

Line of Service
Advisory

Specialism
Deals

Management Level
Associate

Job Description & Summary
A career in our Digital Forensics and eDiscovery (DFeD) practice, within Forensic Technology services, will provide you with the opportunity to help our clients protect their business in today’s evolving landscape by applying advanced and strategic approaches to information management. We focus on assisting organisations manage vast amounts of electronic data and navigate the legal and business processes demanded by critical events which includes litigation, regulatory requests and internal investigations.

Our team helps our clients collect, filter, and review electronic documents to effectively mitigate technological risk and maximise exploitation of their information assets.

Anti Fraud Data Analyst – Managed Services – Deals

At PwC, we are investing in our Execution Managed Services (EMS) business. EMS brings the best of PwC’s advisory capabilities and our operational delivery to help clients solve complex problems. Our Financial Crime team is a critical part of this growth priority area and we are looking for motivated individuals who have a desire/interest to support our clients in delivering some of their most critical operations and programmes.Our EMS team will work with cutting edge technology to provide specialist and complex services to our clients across the region.

What to consider before applying

– This role will be based out of the Jordan office.
– Your flexibility to travel 90% of the time. This means we may require you to work away from your base office location on a regular basis and frequent overnight stays may be required.

Responsibilities

As an Anti Fraud Analyst, you’ll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. Responsibilities include but are not limited to

– Perform analysis on various data sets using advanced data analytics techniques to identify fraud related trends, patterns, scenarios and other valuable business insights
– Use SQL to perform extract, transformation and load for analysis and retrieval purposes
– Design interactive and informative dashboards using data visualization tools such as Tableau and PowerBI
– Design and implement data models for data integrity, quality control and validation controls
– Design, implement and tune data models using statistical analysis and machine learning to identify fraud typologies (payment fraud, identity theft and account takeover)
– Identify opportunities to enhance and optimize the existing process and reporting capabilities in order to improve both the speed and efficiency
– Collaborate closely with clients to understand their business requirements related to fraud analysis
– Continuously monitor the threat landscape by producing actionable recommendations supported with data