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The Data/Information Management Analyst is a strategic professional who stays abreast of developments within their field and contributes to directional strategy by considering their application in their job and the business. Recognized technical authority for an area within the business. Requires basic commercial awareness. Developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers. Significant impact on the area through complex deliverables. Provides advice and counsel related to the technology or operations of the business. Work impacts an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family.
Key Responsibilities:- This function covers incumbents responsible for various data activities, which include database administration, data analysis, maintenance, data quality, and database management or database architecture/design engineering.
- Day-to-day focus is on resolution of complex problems or transactions, where expertise is required to interpret against policies, guidelines or processes.
- Role at this level usually has full ownership for one or more processes, reports, procedures or products, and may also be considered analytical or procedural experts representing a unit or team on cross-functional process or project deliverables.
- May supervise day-to-day work of junior level employees.
- Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citi, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.
- 6-10 years of experience in a quantitative field.
- Excellent analytical and practical problem-solving abilities.
- Solid understanding of the consumer lending market, customer life cycle, and profit and loss statements.
- Experience in segmentation, modeling, and optimization.
- Working experience in the financial/credit card industry.
- Knowledge of analytic tools (SAS E-miner, Knowledge Seeker, SPSS, etc.) and methodologies (regression, CHAID, simulation, etc.).
- Big data and machine learning experiences (R, Python, etc.).
- Bachelor's/University degree, Master's degree preferred.
