Assistant Vice President, Fraud Data Engineer - Hybrid

At Citi, we get to connect millions of people across hundreds of cities and countries every day.  And we've been doing it for more than 200 years.  We do this through our unparalleled global network.  We provide a broad range of financial services and products to our clients – whether they be consumers, corporations, governments or institutions – to help them meet their biggest opportunities and face the world's toughest challenges.

The team is Analytics Innovation that is a global analytics unit under Global Internal Fraud Analytics. The team focuses on conducting the innovation and implementation of data pipeline, data structure, BigData Sandbox, detection routines, advanced algorithms, AI/ML models and Fraud Analytics. The current role is the senior data scientist lead who reports to Internal Fraud Innovation/Analytics Head.

Responsibility

• Under the supervision of Global Internal Fraud Innovation Head, collaborate with a team of core data scientists based globally in advanced analytics innovation and implementation for all regions.

• Assist Regional Internal Fraud Analytics Intelligence teams to perform analysis on latest fraud trend, fraud risk and gap analysis, and review and obtain new data source for fraud detection including data engineering.

• Engage and work closely with Regional Internal Fraud Analytics Intelligence Head, 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.

• Conduct advanced analytics/algorithm research and innovation. Work closely with Regional Intelligence and Ops teams on the delivery of dashboards.

• Work closely with Internal Fraud Governance and Control team on design, implementation, execution and automation of change process, data quality monitoring project.

• Attend evening or night call with stakeholders and technology support teams if needed.

Qualifications

• 5-6 years of work experience.

• 3+ years of experience in data engineering, Hadoop development, advanced analytics or modeling.

• Has project experience on data management such as data pipeline, data structure and data quality governance.

• Experience in fraud analytics and familiar with latest fraud trend in banking industry.

• Proficient in data analytics programming: Spark, SQL, Python etc.

• Proficient in visualization tools such as Power BI, Tableau, QlikView.

• Has AI/ Machine Learning project experience is not a must but a plus.

• Proficient in both spoken and written English.

Education

• Bachelor’s degree/University degree or equivalent experience

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