Lead Machine Learning Engineer

Client Project Opportunity

About the Role

We are looking for an experienced Lead Machine Learning Engineer to develop, deploy and maintain enterprise predictive models that improve account prioritisation, collections effectiveness and payment-risk assessment.

You will own the complete machine learning lifecycle, including data preparation, feature engineering, model selection, validation, production deployment, monitoring and retraining. You will collaborate with business specialists, data engineers and application engineers to integrate reliable and explainable predictions into operational workflows.

Key Responsibilities

• Develop predictive models that estimate the likelihood of customer payment.
• Build models that predict expected payment delays.
• Develop models that assess the risk of credit loss.
• Combine model predictions with account value and account age to support account prioritisation.
• Develop account-prioritisation approaches for scheme and private accounts.
• Create explainable account rankings for business and operational users.
• Develop next-action recommendations that comply with credit policy and operational-team capacity.
• Incorporate collection outcomes into model improvement and retraining.
• Own data preparation and feature engineering for predictive models.
• Evaluate and select appropriate machine learning algorithms.
• Design and execute model validation.
• Work with business specialists to define meaningful evaluation measures and acceptance criteria.
• Deploy models into production scoring workflows.
• Implement model versioning and release controls.
• Implement model-performance monitoring and drift detection.
• Design and maintain model-retraining processes.
• Manage model explainability, reliability and production performance.
• Collaborate with data engineers to obtain reliable model inputs.
• Collaborate with application engineers to integrate predictions into operational workflows.

Must-Have Skills & Experience

• 10+ years of relevant experience in machine learning, data science and enterprise predictive-solution development.
• Strong Python programming skills.
• Strong hands-on machine learning development experience.
• Practical experience using Azure Machine Learning.
• Hands-on experience with MLflow.
• Experience consuming enterprise data from Microsoft Fabric.
• Experience developing predictive classification or risk models.
• Strong feature-engineering and model-validation skills.
• Experience deploying machine learning models into enterprise applications.
• Experience implementing production model-scoring workflows.
• Experience with model versioning, performance monitoring and drift detection.
• Experience designing and operating model-retraining processes.
• Strong understanding of model explainability.
• Proven ability to manage model performance and reliability after production release.
• Experience working with business specialists to define evaluation measures and acceptance criteria.
• Ability to collaborate with data and application engineering teams.

Good to Have

• Experience developing payment-propensity, payment-delay or credit-risk models.
• Experience building account-prioritisation or next-best-action solutions.
• Experience working with collections, financial-services or revenue-management data.
• Experience with Microsoft Fabric and Azure Databricks.
• Experience implementing responsible artificial intelligence and model-governance practices.
• Knowledge of generative artificial intelligence or conversational collection solutions.
• Experience deploying machine learning workloads using CI/CD pipelines.
• Relevant Microsoft Azure or machine learning certification.

Role Details

• Experience - 10+ Years
• Location - India
• Work Mode - Remote
• Employment - Full-time
• Domain - Machine Learning / Predictive Analytics / Payment Risk and Collections