$157.50K - $163.30K/yr
Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Posted 8 days ago
Job description
Duties: Code, test and execute requirements for simple-to-complex Retail Services Partner Delivery data processing programs. Design and construct new data processes using Base SAS, SAS Macros, Advanced SAS, Autosys Job scheduler, Service Now, Bitbucket, SQL, and Unix shell scripts. Modify existing data processes according to new business requirements. Identify and segment Retail Services reporting populations across data sources. Perform functionality testing and generate validation reports for data processes. Validate data from multiple sources to reconcile variances in the attributes and to ensure accurate data is consumed by data processes. Prepare, review, and execute test cases to ensure data processes create accurate results and run as expected. Work with stakeholders to define reporting requirements and iterate with business users to ensure output matches expectations. Consult on data processing solutions and create automated solutions to streamline report and process execution. Prepare data flow charts and process flow diagrams to illustrate transformations and rules to describe logical operations. Ensure support of ongoing activities. A telecommuting/hybrid work schedule may be permitted within a commutable distance from the worksite, in accordance with Citi policies and protocols.
Requirements: Requires a Master's degree or foreign equivalent in Engineering (any), Information Systems, Embedded Systems, Data Science, Computer Science or related field and 4 years of experience as a Developer, Data Analyst, Business Analyst, Business Relationship Manager, Systems Analyst, Software Engineer or related position. Alternatively, employer will accept a Bachelor's degree in the stated fields and 6 years of the specified progressive, post-baccalaureate experience. Full span of experience must include: SAS programming language; Unix operating system and scripting; Working within the Banking sector, including Risk and Compliance; and Working within Credit Card Domain; Writing and interpreting project requirements; AutoSys job scheduler; Bitbucket code change control; Working with large scale databases and files; and Software Development Lifecycle (SDLC), including planning, design, analysis, development, testing and deployment. Applicants submit resumes at https://jobs.citi.com/. Please reference Job ID #26964059. EO Employer.
Wage Range: $157,500 to $163,300
Job Family Group: Technology
Job Family: Data Science
Job Family Group:
Job Family:
Time Type:
Full time
Primary Location:
Schaumburg Illinois United States
Primary Location Full Time Salary Range:
In addition to salary, Citi's offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.
Most Relevant Skills
Please see the requirements listed above.
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
Anticipated Posting Close Date:
Jul 09, 2026
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Analyst?
A: To succeed as a Data Analyst, key technical skills include proficiency in programming languages such as Python or R, expertise in data visualization tools like Tableau or Power BI, and knowledge of statistical analysis and machine learning concepts. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial for presenting insights to stakeholders and working with cross-functional teams. By combining these technical and soft skills, Data Analysts can drive business decisions, identify areas for improvement, and contribute to the growth and success of their organization.
Q: What is the career path for a Data Analyst?
A: A Data Analyst's typical career progression involves starting as an Entry-Level Data Analyst, where they collect, analyze, and interpret data to inform business decisions. As they gain experience, they can move into Mid-Level roles such as Senior Data Analyst or Business Analyst, where they take on more complex projects and lead smaller teams. Ultimately, they can advance to Senior Leadership positions like Data Scientist, Data Manager, or even Director of Analytics, where they oversee large-scale data initiatives and drive strategic business growth.\n\nKey opportunities for skill development and professional growth in this role include learning programming languages like Python or R, mastering data visualization tools like Tableau or Power BI, and staying up-to-date with emerging trends in machine learning and artificial intelligence. Additionally, Data Analysts can develop soft skills like communication, project management, and leadership to excel in their roles.\n\nLong-term career prospects for Data Analysts are diverse, with potential directions including transitioning into related fields like Business Intelligence, Data Engineering, or even becoming a Product Manager, or pursuing advanced degrees in Data Science or related fields to further specialize in areas like machine learning or data engineering.
