Company Overview
At Citi, our mission is to be a trusted partner by delivering responsible financial services that support growth and economic progress. Our key offerings include asset protection, lending, payment processing, and access to capital markets on behalf of our clients. With more than 200 years of experience, Citi has helped individuals, businesses, and institutions navigate complex challenges and seize new opportunities. As a truly global bank, we connect millions of people across hundreds of cities and countries around the world.
Role Responsibilities
-
Analyze and document business requirements for consumer financial products, including credit cards, mortgages, deposits, and loans, ensuring compliance with industry standards and regulatory mandates.
-
Lead and support regulatory reporting initiatives such as CCAR, BASEL, Liquidity, Prudential, and Capital requirements to ensure compliance with evolving frameworks.
-
Collaborate with cross-functional teams to strengthen data governance, enhance automation, and improve reporting workflows, leveraging GenAI and cloud-based platforms where appropriate.
-
Drive continuous process improvements and support the adoption of modern technologies to streamline financial data provisioning and reporting efficiency.
-
Contribute to the development and implementation of data analytics standards used across teams.
-
Use well-developed communication and negotiation skills to influence internal stakeholders and, occasionally, external clients.
-
Resolve complex, variable issues by conducting detailed analysis and recommending appropriate actions when clear solutions are not immediately apparent.
-
Oversee the quality, volume, timeliness, and successful delivery of data science projects, including short-term resource planning.
-
Ensure decisions and practices align with risk management policies, legal and regulatory requirements, and ethical standards. This includes proactively identifying, escalating, and addressing potential control issues.
Required Qualifications
-
5–8 years of experience in statistical modeling, data analytics, or data engineering, particularly with large datasets.
-
Strong analytical, interpretive, and problem-solving capabilities.
-
Solid background in retail banking or finance, particularly with products such as deposits, mortgages, and credit cards.
-
Hands-on experience with big data platforms and ETL tools such as DataStage, Ab Initio, Hive, or Hadoop.
-
Proficiency in relational databases, including the ability to write and optimize complex SQL queries, stored procedures, and performance tuning.
-
Familiarity with regulatory reporting standards, including CCAR and liquidity risk reporting.
-
Excellent interpersonal, verbal, and written communication skills.
Education
-
Bachelor’s degree or equivalent professional experience in a relevant field.