RooCruit Candidate:
Roo0318
Interested in possibly hiring this candidate?
Simply click the link below to book a call with the team
About the Candidate
I am a very highly motivated individual, who is willing to learn and produces work of high standards. I am attentive to detail and can effectively prioritise my work schedule. I enjoy working in a team-oriented environment where individuality is recognised but can still work well independently.
Area of Expertise
Creation of automated daily, weekly and ad hoc reports for the legal collections department using MS Access, SQL,SSIS,SAS and AS400, Uploading of bulk files onto Tallyman and exactus (Banking and collections system), Development and presentation of monthly numbers reports for the Collections business unit to management thus providing support to business partners in the use and interpretation of the applicable reports. Analyzing and providing data/information to management on department’s performance and improvements. Data mining and manipulation. Daily updates and design of dashboards showing financial and collections figures. Analysis of graphs for trends and patterns which are key to the business performance. Conduct data query and ad hoc analysis of existing loan clients.
Experience & Availability
International Experience:
Yes
Availability:
10, 20 or 40 hours a week
Years Experience:
15
Current and Previous Roles:
Relevant Experience
Job Title: Fraud Data Scientist Rapid Payments Programme
Duration: 15
Key Responsibilities:
Implement high performing fraud detection model that meets detection matrix communicated to the industry through the TCS developed Quarts Compliance Fraud Solution.
Perform detailed UAT (Spira) testing on functionality test and fraud detection capabilities and AI functionality.
Run simulation exercises to benchmark expected fraud alert volumes and possible true positives.
Configure Initial fraud detection rules and patterns based on simulation outcomes.
Work with cross departmental teams to define metrics, guidelines, and strategies for effective use of data in fraud detection.
Create data mining, statistical reporting, and data analysis methodologies. (Oracle Qlik, Agile)
Coordinate data resource requirements between analytics and technical teams
Work with product managers, engineers, and analytics team members to translate prototypes into production
Identify fraud patterns through the monitoring of transactions
Complete preliminary investigations or reviews to determine if fraudulent activity is occurring and take necessary action to close accounts as required
Conduct research and make recommendations on big data infrastructure, database technologies, analytics tools, services, protocols, and standards
Drive the collection of new data and the refinement of existing data sources
Develop algorithms and predictive models to reduce frequency of fraudulent transactions
