Role - Offshore Analytics Lead for Internal Fraud . This role is a people manager role , collaborating closely with Global Head of Internal Fraud Analytics Innovation & AIM Lead for Financial Crime and Fraud Prevention.
Responsibility
- Partner with 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
- Responsible for leading and managing a team of data scientists
Qualification-
- 8+ years of work experience in analytics domain in BFSI domain
- Mandatory to have , 2+ years of experience in data engineering, Hadoop development, advanced analytics or modeling.
- Experience in 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 is preferable but not mandatory
- Hands on experience with visualization tools such as Power BI, Tableau, QlikView.
- Has AI/ Machine Learning project experience is not a must but a plus.
- Hands-on experience with Python/Pyspark/Scala and basic libraries for machine learning is required;
Solid SQL skills and understanding of data structure/pipeline
Familiar with Python, PySpark, Big Data and Hadoop. A deep understanding of Apache Spark.
Experience with data analysis, explorative analysis, data engineer
Understanding of Software Development methodologies, Compliance, Governance, control and risk
Familiarity with Unix environment. Shell scripting is not mandatory.
Educational Qualification - Bachelors/Masters in Science, Technology /Engineering ,Economics,Statistics,Mathematics
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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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