Job Description

Innovate:

  • Develop cutting edge not as yet explored solutions
  • Create Impact across businesses: Developed analyses/tools will have impact not only within client's Retail Services but also on businesses across the globe from APAC to EMEA

Learn & Develop:

  • Work with best in-class analytics and leadership team with diverse skills ranging from various statistical technique including machine learning, text mining, etc.

Move and Grow:

  • The leadership team is focused on career mobility of its individual team members which will enable the candidate to build a career both horizontally as well as vertically i.e. across geography (APAC, EMEA, North America), across businesses (Retail Bank, North America Branded cards, etc.), across domains (Data Sciences, Analytics, Reporting, Operations), across functions (Risk, DM, Marketing)

Culture:

  • Work in a fast-paced culture that is dynamic, aspirational, fun-loving but at the same time fosters a work-life balance

Role & Responsibilities:

 

Business/Department Objectives:

  • Provide analytic support to the business teams, understand the business context and formulate and execute appropriate analytical approach(es) to address the business situation. Independently manage end to end partner communication

Core Responsibilities:

 

Delivery ownership/Relationship Management:

  • Lead business delivery across multiple complex solution and Interact regularly with Partner leadership to set and manage expectations aligned to group capabilities and work to deepen existing relationships

Planning:

  • Develop and communicate strategic and operational goals and plan for the team

Talent Management:

  • Own resourcing strategy for the team and help GDM leaders to balance resource allocation across the site

Organizational Development:

  • Institutionalize analytic learnings across the site. Anticipate business demands and undertake initiatives to develop site capabilities aligned to the business requirements

Communication:

  • Effectively communicate strategic considerations with team, partners and senior management

Day-to-Day Responsibilities:

  • Collaborate with business teams to understand the challenges and innovatively come up with solutions to meet their requirements
  • Provide technical leadership and subject matter expertise to enable build best in class solutions
  • Keep abreast of the latest developments in the analytic space across industries for potential uses
  • POC Execution: Work on multiple project/unstructured problems businesses are facing across markets, look at providing solutions that go beyond traditional methods – Using advanced technologies and new data sources 

Financial/Budgetary: No

 

Individual Contributor (IC)/Managerial: Managerial

 

Key Deliverables:

  • Proven problem solving skills in industrial settings is a must
  • Proven ability in model building and application experience in data mining techniques and tools (SAS and/or other modeling packages)
  • Competent leadership skills of high quality Talent
  • Understanding of financial domain is preferred 
  • Ability to translate and articulate thoughts and ideas to a larger audience including influencing skills with peers and senior management
  • Proven ability to implement advanced technical solutions in the business operational environment
  • Self-motivated to continuously upgrade one’s domain knowledge, keep abreast of latest developments in the field and evaluate its application in the business area on a consistent basis
  • Exceptional commitment to stay focused in one’s pursuit towards excellence with demonstrated results of the same

Education:

  • Field of post-graduation – Economics, Statistics and Economterics ,Computer Science, Mathematics, Operations Research, Management Science and related

Experience:

  • Experience in the field of advanced quants while working for leading analytics organizations of large corporates or in consulting companies in analytics roles
  • Exposure to Statistical modeling and tools
  • Led high quality teams
  • Exposure to Machine Learning Algorithms – preferred not must fields. Could be any graduate degree holder