Citi Assistant Manager in Mumbai, India

  • Primary Location: India,Maharashtra,Mumbai

  • Education: Bachelor's Degree

  • Job Function: Risk Management

  • Schedule: Full-time

  • Shift: Day Job

  • Employee Status: Regular

  • Travel Time: No

  • Job ID: 16007630


  • Position Title: Assistant Manager

  • Grade/Level: C10

  • Business Group: CSIPL

  • Function/Group: Citi Retail Services – Risk Strategy and Integration

  • Department: Risk Strategy and Integration-COE

  • Location: Mumbai

Roles and Responsibilities

Business/Department Objectives:

  • Enhance and improve the Risk policies using statistical techniques to optimize business growth and profits by minimizing the losses

Core Responsibilities:

  • Support tactical and strategic Risk Analytics projects for Citi’s Retail Services Group in the US

  • Partner with Risk Management Policy teams and Operations amongst others to support the Interaction Management model to improve risk processes and policies throughout the customer lifecycle

  • Apply innovative analytical techniques to customer and transaction data to build risk mitigation strategies and process enhancements

  • Effectively provide updates and communicate key initiatives to senior risk management

  • Analyze tests and performance using SAS and decision tree methodologies (CHAID/CART)

  • Evaluate effectiveness of current policies and strategies

  • Interact and communicate effectively and build strong working relationships on an ongoing basis with business partners

  • Contribute in center management activities in Mumbai CoE

Day-to-Day Responsibilities:

  • Support the expanding challenges and complexities of the interaction model among our customers and risk processes and policies throughout the customer lifecycle

  • Focus more holistically and deeply on enhancing effectiveness and identifying/realizing efficiencies in our policies and processes

  • Clearly communicate analysis

  • Presentations to both technical and non-technical personnel are required to be made frequently as part of the job

  • Provide insight into the data through MIS and deeper analytics

  • Summarize analytic reports into presentations and share analyses and reports with senior leadership

  • Work efficiently in a matrix environment balancing between both business and functional interactions and priorities

Financial/Budgetary :NA

Individual Contributor (IC)/Managerial: IC

Key Deliverables:

  • Clearly formulate analytical hypothesis

  • Perform ad-hoc analysis to support the hypothesis, communicate results clearly, and understand cause and effect relationships

  • Support approved strategies through implementation

  • Ability to manage multiple priorities

  • Effectively interact with business partners across functions including risk policy, credit, fraud and customer service operations, technology, product management amongst others

Percentage of Travel: No

Relocation: No




  • Bachelor’s or Master’s degree in a quantitative discipline: Mathematics, Economics, Operations Research, Statistics


  • 4+ years related work experience required, with significant academic experience/contribution


  • Strong understanding of Credit policies

  • Strong analytical skills in conducting sophisticate analysis using bureau/vendor data, customer performance data and marketing data to solve business problems

  • Good programming skills in advanced SAS and SQL in mainframe, UNIX and PC environments

  • Highly proficient in Excel/pivot tables and PowerPoint

  • Good written English


  • Exposure to project/process management

  • Strong communication and presentation skills targeting a variety of audiences

  • Ability to work with cross functional teams

  • Create and sustain a network of strong client relationships

  • Flexibility in approach and thought process

  • Ability to work effectively across portfolio risk policy teams and functional areas teams

  • Strong influencing, negotiating, and facilitation skills

  • Analytical mindset



  • Credit card industry experience especially in an analytics or policy role is preferred

  • Programming skills in R

  • Exposure to machine learning techniques

  • Some policy writing experience