Manager

Manage risk analytics projeBuild predictive models for real-time fraud detection systems.

Evaluate and optimize existing ML models for performance, scalability, and explainability.

Apply deep learning and advanced analytics for behavior analysis and risk profiling.

Analyze transaction data to identify patterns, anomalies, and fraud trends.

Perform exploratory data analysis (EDA) to understand customer behavior and potential fraud vulnerabilities.

Translate data-driven insights into actionable recommendations for leadership and stakeholders.

Collaborate with fraud strategy and operations teams to enhance fraud prevention frameworks.

Validate and monitor predictive models for real-time fraud detection systems using valid monitoring metrics/KPI’s.

Prepare technical documents related to fraud models and model validation. Validate the models using various techniques and KPIs, out of time validation etc.

Set up monthly/quarterly and annual monitoring for the models using valid monitoring metrics/KPI’s.

Perform Root Cause Analysis in case of deterioration of model performance/data issues.

Evaluate and optimize existing ML models for performance, scalability, and explainability.

Apply deep learning and advanced analytics for behavior analysis and risk profiling as part of

Analyze transaction data to identify patterns, anomalies, and fraud trends.

Perform exploratory data analysis (EDA) to understand customer behavior and potential fraud.

Translate data-driven insights into actionable recommendations for leadership and stakeholders.

Collaborate with other teams like fraud strategy to enhance fraud prevention frameworks.cts. Ensure adherence to policies. Provide strategic guidance. Lead a team.

Hands on experience in Graph Knowledge Database / Graph Neural Networks based solutions.

Handle the requests coming from client on Graph Knowledge Databases

Provide solutions and mentor the team working with her/him on the graph solutioning