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;
- 7+ years in Data Science / Data Analytics, including 4+ years in Banking/Financial Services;
- Strong expertise in Hive, Impala, Python (Pandas, NumPy, Scikit-learn), R, SQL, and PySpark;
- Experience in ML frameworks - preferred but not mandatory;
- Hands-on experience with Qlik Sense and Big Data tools (Hadoop, Spark, Hive/Impala);
- Experience building ETL pipelines and end-to-end analytical workflows;
- Strong understanding of machine learning, including unsupervised models (K-Means, DBSCAN, GMM, Isolation Forest, One-Class SVM, LOF);
- 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
- Lead end-to-end analytics on Hadoop Big Data (Spark/Hive): data ingestion, EDA, feature engineering, model development, validation, deployment, and monitoring;
- Develop models for AML, fraud analytics, anomaly detection, customer segmentation, and risk scoring using supervised and unsupervised ML;
- Create analytical workflows, automations, and pipelines;
- Prepare high-quality documentation: Functional Specification Documents (FSD), Model Design Documents (MDD), Business Impact Analysis (BIA), and testing packs;
- Build dashboards and reports using Qliksense and communicate insights clearly;
- Lead stakeholder meetings, facilitate workshops, and deliver executive-ready presentations with strong narrative clarity;
- Translate business requirements into actionable analytical solutions and recommend data-driven strategies;
- Ensure compliance with model governance, data quality, and security standards;
- Mentor junior analysts and data scientists, fostering best practices in analytics and model development.
Should you be interested in this career opportunity, please send in your updated resume to [Confidential Information] at the earliest.
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Confidentiality is assured, and only shortlisted candidates will be notified for interviews.
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