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Tier-1 brand, mid-level Data Scientist title, metro location, and broad ML/AML skillset increases competition.
Role requires AML and financial services domain knowledge, limiting cross-industry transferability.
Explicit 4+ years, AML/financial domain experience and specific ML/tech stack make filters strict.
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Lead development and implementation of ML/AI/Gen AI solutions to detect suspicious AML transaction activities.
Analyze transaction data using advanced statistical methods and communicate findings to business partners and senior leaders across global geographies.
Maintain data quality, automate data processes, and document analytical solutions to enhance AML detection capabilities.
4+ years experience in Financial Services or Analytics Industry.
Proficiency in Python, SQL, Hive, and advanced programming with big data tools (e.g., Spark, Hue, Impala).
Master's degree in a numerate subject (Mathematics, Operational Research, Economics, Business Administration) from a premier institute or equivalent performance.
Experience with AI, Gen AI, and statistical modelling relevant to AML/financial crime analytics.
Experienced in AML transaction monitoring within banking or financial services environment.
Comfortable collaborating across multiple geographic regions and communicating complex analytics to technical and non-technical stakeholders.
Strong quantitative and statistical background with practical skills in developing and deploying cutting-edge AI/ML models for financial crime detection.