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High due to Tier-1 bank brand, mid-level generalist Data Scientist role, Bengaluru metro, and broad skill requirements.
Medium because core data science skills transfer across industries though financial-crime domain knowledge is advantageous.
High because of explicit 5+ years requirement and mandatory production ML, PySpark, and AWS skills.
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Lead development and deployment of AI/ML models targeting financial crime use cases including AML, fraud, scams, and risk intelligence.
Handle large-scale structured and unstructured datasets using Python, SQL, PySpark to build scalable data and ML pipelines and cloud-native AI solutions on AWS.
Collaborate cross-functionally with data scientists, engineers, and domain experts to innovate and deliver impactful AI solutions while supporting model deployment and continuous improvement.
5+ years of experience in Data Science, Machine Learning or Applied AI.
Proficiency in Python, PySpark, SQL, and AWS for developing and deploying ML models at scale.
Experience with large-scale dataset processing and production ML environments.
Bachelor’s, Master’s, or PhD in Statistics, Mathematics, Data Science, Computer Science, or related field.
Experienced in financial crime domains such as AML, fraud, risk, or banking environment.
Skilled in building, evaluating, and deploying generative and agentic AI systems.
Capable of operating in cross-disciplinary teams involving engineering, product, and domain experts to solve complex problems at scale.