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High due to Tier-1 brand, metro Bangalore location, mid-level 2-4 years, and generalist analytics skillset.
High because the role requires AML and financial services domain expertise, limiting cross-industry transferability.
High because of explicit 2–4 years requirement, premier-institute preference, and mandatory Python/SQL/Hive and statistics skills.
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Own threshold tuning and optimization efforts, including Logistic Regression model development and performance review to predict customer behavior and detect anomalies.
Segment customers into homogeneous groups using clustering techniques and conduct outlier detection for AML data science projects.
Collaborate across geographies to analyze data, prepare reports, automate data processes, and develop transaction monitoring scenarios to support financial crime risk management.
2-4 years of experience in Financial Services or Analytics Industry.
Master's degree in a numerate subject such as Mathematics, Operational Research, Business Administration, or Economics from a premier institute.
Proficiency with Python, SQL, Hive and strong statistical and data analytics background.
Experience in threshold tuning, logistic regression modeling, clustering, anomaly detection, and financial services domain including AML preferred.
Experienced in financial services analytics with demonstrated ability to apply quantitative and qualitative analysis methods to AML and transaction monitoring.
Capable of operating independently on multiple workstreams with flexibility to shift priorities based on business needs.
Skilled in communicating complex statistical concepts clearly to non-technical audiences and preparing formal documentation with statistical vocabulary.