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Accenture is seeking a Fraud Analytics professional to lead end-to-end analytics engagements for financial services clients, including model development, validation, and implementation. The role emphasizes advising CXOs on fraud initiatives and developing PoCs to win opportunities.
The candidate should have 3-5 years of fraud analytics experience, strong programming skills, and familiarity with leading analytics tools. Travel up to 40% may be required.
Engagement Execution Work independently/with minimal supervision in client engagements that may involve model development, validation, governance, strategy, transformation, implementation and end-to-end delivery of fraud analytics/management solutions for Accenture’s clients. Advise clients on a wide range of Fraud Management/ Analytics initiatives. Projects may involve Fraud Management advisory work for CXOs, etc. to achieve a variety of business and operational outcomes. Develop and frame Proof of Concept for key clients, where applicable Practice Enablement Guide junior team members. Support development of the Practice by driving innovations, initiatives. Develop thought capital and disseminate information around current and emerging trends in Fraud Analytics and Management Support efforts of sales team to identify and win potential opportunities by assisting with RFPs, RFI. Assist in designing POVs, GTM collateral. Travel: Willingness to travel up to 40% of the time Professional Development Skills: Project Dependent
3-5 years of relevant Fraud Analytics experience at one or more Financial Services firms, or Professional Services / Risk Advisory with significant exposure to one or more of the following areas: Banking Fraud, Payment Fraud, Credit Card Fraud, Retail Fraud, Anti Money Laundering, Financial Crime, Telecom Fraud, Energy Fraud, Insurance Claims Fraud etc. Advanced skills in development and validation of fraud analytics models, strategies, visualizations. Understanding of new/ evolving methodologies/tools/technologies in the Fraud management space. Expertise in one or more domain/industry including regulations, frameworks etc. Experience in building models using AI/ML methodologies. Modeling: Experience in one or more of analytical tools such as SAS, R, Python, SQL, etc. Knowledge of data processes, ETL and tools/ vendor products such as VISA AA, FICO Falcon, EWS, RSA, IBM Trusteer, SAS AML, Quantexa, Ripjar, Actimize etc. Strong conceptual knowledge and practical experience in the Development, Validation and Deployment of ML/AL models Hands-on programming experience with any of the analytics tools and visualization tools (Python, R, PySpark, SAS, SQL, PowerBI/ Tableau) Knowledge of big data, ML ops and cloud platforms (Azure/GCP/AWS) Strong written and oral communication skills Project management skills and the ability to manage multiple tasks concurrently Strong delivery experience of short and long term analytics projects
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