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Advanced Analytics Manager Analytics and Modeling Group

5.00 to 6.00 Years   Mumbai City   18 Jun, 2019
Citibank India
Job LocationMumbai City
EducationNot Mentioned
SalaryNot Disclosed
IndustryBanking / Financial Services
Functional AreaStatistics / Analytics
EmploymentTypeFull-time

Job Description

Business/Department Objectives:

  • This role resides in the Advanced Analytics team which is part of the Global Fraud Prevention Analytics & Modeling organization, responsible for leveraging the latest analytical tools, techniques and big data to enhance fraud detection and mitigation capabilities for the Global Consumer Business. A key component is the teams capability is the Entity Linkage Framework (ELF), an award-winning big data application of graph theory and network analytics that enables unprecedented views of defined relationships
Core Responsibilities:
  • Conceptualize and execute Fraud Prevention Big Data initiatives across all GCB Lines of Businesses (LOBs)
  • Make the most effective use of the available Big Data infrastructure and Data Science techniques to address Fraud Risk Management challenges and implement optimal technical solutions
  • Partner closely with variety of cross-functional teams (e.g. Risk Policy, Fraud Strategy, Data Intelligence, IT/Infrastructure, Operations) to drive initiatives forward
  • Build effective presentations to communicate complex analysis and findings suitable for a wide array of audiences
  • Proactively plan and prioritize work according to criticality and shifting priorities/strategies, while balancing need to drive longer-term initiatives
  • Mentor and coach junior team members
  • Note that working hours will be modified to support US and other regional-centric requirements
Financial/Budgetary: NAIndividual Contributor (IC)/Managerial: Individual ContributorPercentage of Travel: NoRelocation: Yes, *Qualifications:Required:Education:
  • Bachelor s Degree required in statistics, mathematics, engineering, computer science, physics, economics, or related quantitative discipline from a premier institution
Preferred:Education:
  • Master s degree in statistics, mathematics, engineering, computer science, physics, economics, or related quantitative discipline from a premier institution
Experience:
  • 5+ years of relevant work experience
  • Strong understanding and experience working with machine learning algorithms, unstructured data and network science
  • Expertise on digital/online/mobile processes and understanding of related cyber/fraud risks
  • Enterprise experience working with Digital, Big Data mining tools and technology preferred
  • Experience with end-to-end project or process management
  • Experience working in a large, sophisticated credit granting organization with major credit card, financial services, retail or consulting business a plus
Skills:
  • Excellent quantitative and analytic skills and data-driven mindset; ability to derive patterns and formulate sound analytical constructs to test different hypothesis
  • Hands-on experience working with large datasets on a Big Data platform like Hadoop stack (MapReduce & Spark) or AWS; strong programming experience in Python, R & SAS
  • Hands-on experience working with large datasets on a Big Data platform like Hadoop stack a plus
  • Effective in partnering with cross-functional teams and creating/sustaining network of strong client relationships
  • Excellent communicator with strong written and verbal communication skills; ability to create and deliver compelling presentations, translating complex material into narrative suitable to a variety of audiences
  • Solutions-oriented can do attitude, with ability to challenge status-quo and drive innovation via thought leadership while maintaining end-to-end view
  • Ability to prioritize work and make decisions independently with limited guidance from management
  • Extremely detail-oriented, with strong; intellectual curiosity. Ability to set and meet high standards

Keyskills :
analyticssqladvancedexceladvertisingandroidenvironmentalimpactassessmentdataminingriskmanagementfrauddetectioncomputersciencemachinelearningarietyofaudiencesbigdatadatasciencegraphthenetwkscience

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