Key Responsibilities –

• Design, Develop and implement Fraud detection models using statistical, machine learning, and AI techniques.

• Evaluate and select appropriate algorithms and modeling techniques based on the nature of the business problem and available data.

• Perform hyperparameters tunning to optimize model performance.

• Create and select relevant feature extraction that improves accuracy and robustness of fraud detection models.

• Conduct rigorous validation and testing of models to ensure they meet performance criteria and risk management requirements.

• Use cross validation and other techniques to assess model generalization.

• Take end to end ownership of model development lifecycle start with data preparation, model development, model deployment and model documentation for appropriate approvals.

• Mentor junior team members and provide technical guidance.

• Write and maintain comprehensive documentation for models and algorithms.

• Present findings and project progress to stakeholders and management.

• Manage Model governance related responsibilities.

Qualifications –

• Bachelor’s or master’s degree in Statistics, Economics, computer science or a related field. A Ph.D. is a plus.

• 8+ years of experience in Model development and governance.

• Strong proficiency in Python and AI/ML techniques.

• Proven track record of building and deploying Machine learning models in production environments.

• Solid understanding of machine learning algorithms, data structures, and software engineering principles.

• Excellent problem-solving skills and the ability to work independently and as part of a team.

• Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Preferred Skills –

• Model development with explainability.

• Familiarity with Model Risk Management and regulatory approvals.

• Contributions to open-source projects or published research in top-tier conferences/journals.

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