The Data Quality Intmd Analyst is a developing professional role. Deals with most problems independently and has some latitude to solve complex problems. Integrates in-depth specialty area knowledge with a solid understanding of industry standards and practices. Good understanding of how the team and area integrate with others in accomplishing the objectives of the subfunction/ job family. Applies analytical thinking and knowledge of data analysis tools and methodologies. Requires attention to detail when making judgments and recommendations based on the analysis of factual information. Typically deals with variable issues with potentially broader business impact. Applies professional judgment when interpreting data and results. Breaks down information in a systematic and communicable manner. Developed communication and diplomacy skills are required in order to exchange potentially complex/sensitive information. Moderate but direct impact through close contact with the businesses' core activities. Quality and timeliness of service provided will affect the effectiveness of own team and other closely related teams.
Responsibilities:
- Perform daily/weekly/monthly variance and data quality analysis as needed to ensure data required for key finance and risk calculations and reporting is of the highest quality
- Identify data quality issues in end to end processes
- Assist with initiatives for effective resolution and improvement of the data.
- Analyze consumer data demand for Credit risk and cross-functional data and assist with identification of critical data elements for critical processes and regulatory reporting in partnership with consumers
- Identify data quality problems and initiatives for effective resolution and improvement of the data.
- Anticipate potential issues by analyzing high materiality variances.
- Participate in meetings covering data quality projects (daily, weekly, monthly)
- Prepare meeting materials and updates for consumers
- Participate actively on Issue Management Resolution meeting
Qualifications:
- 2-5 years in Risk/Banking/Finance role.
- Regulatory Reporting knowledge
- A comprehensive knowledge of Finance and Risk principles and data, including data elements, processes
- Strong verbal and written communication skills
- Strong data analysis and problem-solving skills
- A high competency level with MS Access/Excel/Project
- Knowledge of reporting tools like Cognos is preferable
- Ability to work with various organizations.
- High level of attention to detail
- Knowledge/familiarity of Citi’s Risk/Finance systems (for e.g. Optima, Genesis) is preferable
- Ability to work on multiple tasks with conflicting demand/timelines.
- Excellent client focus
Education:
- Bachelor’s/University degree required (preferred in Financial/Accountancy/IT discipline)
- Data management training recommended
What we offer:
- Work in a challenging area of the financial industry with one of the world's leading companies with exposure to variety of products, processes and controls
- Cooperation with a high quality, international, multicultural and global team
- Work in a friendly and diversified environment, appreciating differences in style and perspective and using them to add value to decisions leading to organizational success
- Management supporting balanced and agile work (flexible working hours, home office)
- Attractive benefits package (Benefit System, medical care, pension plan etc.)
- A chance to make a difference with various affinity networks and charity initiatives
The Data Services team is part of Chief Data Office.
The team is comprised of professionals with subject matter expertise on the key attributes of Finance and Risk products and reporting. The team analyses trends and works closely with internal stakeholders to improve the integrity of the data, processes and systems that impact data quality.
The purpose of the job is to monitor the data integrity and quality of data used by Wholesale Credit Risk and Finance Management and Reporting through the analysis of key inputs and outputs of critical processes.