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Tier-1 bank, metro location, mid-level generalist data role increases competition.
AML and financial services focus makes skills less transferable across industries.
Explicit 2-4 years requirement plus mandatory Python/SQL/Hive and AML-domain expectations make filters stringent.
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Own threshold tuning and optimization efforts including anomaly detection, logistic regression modeling, and customer segmentation via clustering techniques.
Perform advanced statistical analysis, data validation, and automation of data extraction and preprocessing tasks to support AML and financial crime analytics.
Collaborate with global business partners and prepare clear documentation and presentations for both technical and non-technical audiences.
2-4 years experience in Financial Services or Analytics Industry.
Master's degree in Mathematics, Operational Research, Business Administration, Economics or related numerate discipline from a premier institute or demonstrable equivalent ability.
Strong Python, SQL, Hive skills; experience in statistics, data analytics, and quantitative methods.
Work Experience Required: 2-4 years; Notice period: Not explicitly mentioned in the JD.
Experienced in AML or financial crime analytics within banking or financial services environments.
Operates effectively in a dynamic, multi-project environment with capability to switch between work streams as business needs change.
Strong communicator able to present complex statistical insights clearly to both technical and non-technical stakeholders globally.