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High: Tier-1 brand, generic Data Scientist title, mid-level experience, metro location, broad ML/GenAI requirements.
Medium — core ML skills transferable, but AML and banking domain knowledge are strongly preferred.
High due to explicit 4+ years, required ML/GenAI proficiency, and mandatory Python/SQL/Spark skills.
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Develop and implement ML/AI/Gen AI solutions for AML transaction monitoring to identify suspicious activities.
Analyze transaction data using advanced statistical and AI techniques and communicate findings to business partners and senior leaders across geographies.
Maintain expertise in AML detection tools, validate data quality, automate data processing, and document solutions clearly for technical and non-technical audiences.
4+ years of experience in Financial Services or Analytics industry.
Strong knowledge of AI, Gen AI, ML/DL/Gen AI algorithms, and statistical modeling.
Proficiency in Python, SQL, Hive, and experience with big data tools (Hue, Impala, Ozzie, Spark).
Master's degree in numerate fields like Mathematics, Operational Research, Business Administration, or Economics from a premier institute.
Experienced in AML domain within banking/financial services, especially transaction monitoring.
Able to effectively communicate complex analytical concepts to technical and non-technical stakeholders.
Skilled at handling large data manipulation processes, data validation, and collaborating with technology teams to address data quality issues.