The Specialized Analytics Ld Data Engineer

As part of the Internal Fraud Analytics, this role executes the fraud analytics and strategies supporting Citi’s North American internal fraud detection. This includes leveraging data to identify internal fraud opportunities, designing and implementing strategies to detect internal fraud and violation of code conduct.

This role partners closely with Internal Fraud Operations, Prevention team and technology partners to align of business and technology direction in order to determine potential and existing internal fraud impacts and carry out whole cycle of implementation. Requires good analytical skills to filter, prioritize and validate potentially complex and dynamic material from multiple data sources. Excellent communication and diplomacy skills are required.

Responsibilities:

Lead design, develop, implement, and support new and existing complex rule logic based on understanding of data and fraud scenario.
Leverage data and advanced analytics to derive patterns, trends and insights, and perform risk/reward trade-off analysis.
Support the timely and accurate delivery of sandbox implementation and simulation of all detective routines, as well as following up with regional technology development and support team on the testing and deployment of the routines in Production environment.
Keep gaining domain and data knowledge.
Generate and manage regular and ad-hoc reporting to enable effective investigation and identification of detection possibilities.
Develop technology documentation to support production deployments as well as ongoing maintenance of reporting and data solutions.
Troubleshoot, diagnose, and resolve data quality and performance issues.
Support technical and analytic needs for control risk and audit activities.

Qualifications:

Bachelor’s Degree required in statistics, mathematics, physics, economics, or other analytical or quantitative discipline. Master's Degree or PhD preferred.
10+ years of experience in data analytics, data engineer and analytical project implementation.

Experience:

8 years of big data environment with hands on coding experience. Solid SQL and Python is required. Pyspark experience is valued.
Excellent exploratory analytic skills: hands-on data validation skills and business analysis acumen to derive patterns and insights and perform risk/reward trade-off analysis.
Creative problem-solving skills; intellectual curiosity; highly detail oriented.
Deep understanding of data management such as data pipeline and data quality.
Must be able to work independently, take ownership of projects, and drive them to completion in a loosely structured setting.

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

#LI-NC2

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Job Family Group:

Decision Management

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Job Family:

Specialized Analytics (Data Science/Computational Statistics)

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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