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14/09 Pratiksha Dhore
Recruiter at Credence HR Services

Views:220 Applications:16 Rec. Actions:Recruiter Actions:5

AVP - Fraud Analytics - Consumer Credit (6-10 yrs)

Hyderabad Job Code: 1154953

Roles and Responsibilities

- Develop, implement, monitor and provide performance tracking of acquisition fraud strategies that minimize and client's fraud risk

- Complete required strategy documentation and meet audit standard

- Work closely with implementation team to ensure strategy is implemented correctly through pre and post implementation validation

- Drive enhanced strategy using champion/challenger learnings to reduce fraud and improve customer experience

- Support new clients onboarding, evaluate and provide recommendation on new tools and process

- Proactively research and identify areas of opportunity for improvement, work closely with the Fraud Operations team to identify recent fraud patterns, trends and rings associated with all Credit portfolios.

- Perform model validations and ensure strategy governance

- Provide direction and support to other team members including mentorship

- Coordinate and communicate on a frequent basis with cross-functional team members

- Meet assigned deadlines and perform tasks as assigned

- Provide thought leadership in various initiatives/projects

- Work on a number of different projects simultaneously, of varying complexity and length. Establishing priorities and coordinating work

- Proactively manage efforts to maintain stakeholder satisfaction, and quantify project benefits delivered.

Qualifications / Requirements

- Masters or Ph.D. in Mathematics/Statistics, Operations Research, Economics, Computer Science/Engineering or other quantitative majors, or equivalent experience beyond Bachelors degree.

- Minimum 8+ years of experience in Analytics domain with at least 5 years in Consumer Credit / Fraud Analytics environment.

- Minimum 3+ years of experience managing end to end project management

- Strong knowledge & hands-on experience of Logistical/Linear/Regressions CHAID/CART/Clustering techniques, Optimization

- Solid working knowledge of SAS, SQL, Unix, MS Office suite. Knowledge on Python, R would be an added advantage

- Deep experience with various Credit/Fraud Risk modeling & strategy building methodologies in a development role.

- Big-picture understanding of Credit Risk & ability to communicate with business and technical stakeholders.

Women-friendly workplace:

Maternity and Paternity Benefits

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