Back
Tier-1 employer, mid-level generalist role in Bangalore with popular data skills.
Requires AML and banking analytics experience, limiting cross-industry transferability.
Explicit 2-4 years plus required Python, SQL, Hive and AML domain knowledge.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead threshold tuning and optimization projects focused on AML transaction monitoring models including Logistic Regression and clustering for customer segmentation.
Analyze transaction and customer behavior to identify anomalies and outliers, validate data quality and automate data preprocessing tasks.
Collaborate globally with business partners to generate actionable insights, document findings, and support financial crime risk detection enhancements.
2-4 years of experience in Financial Services or Analytics industry, preferably with financial services like retail, commercial or institutional banking.
Master's degree in Mathematics, Operational Research, Business Administration, Economics, or related numerate fields from a premier institute or demonstrated equivalent ability.
Proficient in Python, SQL, Hive, and strong statistics and quantitative data analytics background.
Experience with threshold tuning, logistic regression model development and performance review, anomaly detection, customer segmentation using clustering; knowledge of prompt engineering and generative AI is required.
Experienced in AML or financial crime risk analytics within banking or financial services domain with direct exposure to transaction monitoring.
Strong analytical mindset with ability to work on varied data science methods including optimization, segmentation, and statistical modeling.
Capable of working in a global matrix environment, comfortable with cross-geography collaboration and explaining complex data insights to non-technical stakeholders.