Job Summary

We are looking for a Data Analyst to drive end-to-end analytics for Anti-Financial Crime projects in a reputed bank . This role blends strong analytical and data science capabilities with compelling storytelling, documentation excellence, and stakeholder leadership. You will work extensively on Hadoop Big Data, design analytic workflows, build ML models (including unsupervised techniques), and translate insights into meaningful business impact.

Mandatory Skill-set

• Bachelor’s/Master’s in Data Science, Statistics, Computer Science, Mathematics, Economics, or related fields;
• Must have 3+ years in Data Analytics, including exposure in Banking/Financial Services;
• Must have hands-on experience with Qlik Sense and Big Data tools;
• Strong expertise in SQL, Python ( Pandas, NumPy, Scikit-learn ) and PySpark;
• Strong understanding of machine learning, including unsupervised models;
• Excellent communication, consulting, slide creation, and stakeholder storytelling skills.

Desired Skill-set

• Certifications in Data Science, Cloud Technologies, or AML/Compliance;
• Experience in customer segmentation, anomaly detection, and analytics for financial crime;
• Understanding of model risk and regulatory expectations for model governance.

Responsibilities

• Analyze and work with business units on reported issues/queries relating to compliance surveillance systems;
• Process and analyze data related to AML/CFT investigations;
• Tuning and optimization of compliance surveillance systems;
• Tuning and optimization of Machine Learning Models in Compliance;
• Participate in compliance projects for compliance surveillance systems support and support in processing analytics data;
• Demonstrate proactive learning and adaptability to stay informed about regulatory changes and advancements in compliance technology;
• Effectively manage time and prioritize tasks to meet deadlines while maintaining high-quality outputs.

Should you be interested in this career opportunity, please send in your updated resume to [email protected] at the earliest.

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