This role drives end-to-end analytics for Anti-Financial Crime projects within a reputed bank using Hadoop Big Data technologies
Job Summary
This role drives end-to-end analytics for Anti-Financial Crime projects within a reputed bank using Hadoop Big Data technologies.
The successful candidate will design analytic workflows, build supervised and unsupervised ML models, and translate insights into meaningful business impact.
Responsibilities include creating high-quality documentation, building dashboards in Qlik Sense, and leading stakeholder meetings with executive-ready presentations.
Matching Summary
Match Score: 85
This role drives end-to-end analytics for Anti-Financial Crime projects within a reputed bank using Hadoop Big Data technologies.
Skills & Requirements
Must-have
7+ years Data Analytics experience
4+ years Banking/Financial Services
Hadoop Big Data tools (Spark/Hive)
Python Pandas NumPy Scikit-learn R PySpark
Unsupervised ML models K-Means DBSCAN
Nice-to-have
Qlik Sense dashboard creation
AML compliance and regulatory knowledge
Model risk governance understanding
Customer segmentation expertise
Mentoring junior analysts
Key Requirements
Bachelor's or Master's in Data Science, Statistics, CS, Math, Economics
7+ years total Data Analytics experience
4+ years experience specifically in Banking or Financial Services