About the Company

About Essex Lake Group LLC:
With global headquarters in New York, U.S.A. and operations in India, Canada, China and the United Kingdom, Essex Lake Group LLC (“Essex”) delivers transformative profit enhancing solutions, anchored on insights from Big Data, Advanced Analytics and its extensive executive and industry experience. Essex’ customized battle-tested solutions deliver a measurable positive impact within 6 to 18 months. Essex solutions have created substantial profit increases for clients in the areas of revenue growth, cost reduction, consumer and enterprise risk management regulatory compliance. Every Essex solution is customized for the client and the specific problem or opportunity. Essex has proven success and specific experience in the Financial Services, Retail Banking, Telecommunications, Insurance, Healthcare and Media & Entertainment industries, as well as others. Essex delivers visibility in complex businesses to help clients make sound business decisions and its experienced industry experts work with clients through full implementation of its solutions to ensure the organization receives all the benefits from its solutions and methodologies. Further information on the company can be found on its website: www.essexlg.com

About the Role

Operationalize, deploy and monitor machine-learning models developed by data-science teams for banking-domain applications. Build reliable production workflows, manage model releases and track model performance to support ongoing business use.

Responsibilities

• Position

ADG Senior Analyst (ML Ops-Model Deployment & Monitoring)

• Experience

3-5 Years

• Location

Gurgaon, India

• Work Mode

Work from Office (Monday- Friday)

• Time

2:00 PM – 11:00 PM IST

Role Summary Operationalize, deploy and monitor machine-learning models developed by data-science teams for banking-domain applications. Build reliable production workflows, manage model releases and track model performance to support ongoing business use.

Key Responsibilities

Partner with data scientists to package models and prepare them for production deployment
Deploy models for batch scoring or real-time inference based on business requirements
Develop production scoring and supporting data pipelines using Python and PySpark
Automate deployment validation, versioning and release workflows
Manage model artifacts, dependencies, configurations and deployment history
Monitor model performance, data drift, scoring failures and operational reliability
Implement alerts, troubleshooting procedures, rollback mechanisms and recovery processes
Support approved model refreshes and redeployment in collaboration with model owners
Work with technology, security and model-governance teams to meet enterprise requirements
Maintain deployment documentation, monitoring controls and operational runbooks

Qualifications

Required Skills

Required Skills & Experience

Strong hands-on proficiency in Python and PySpark
Practical experience operationalizing and deploying machine-learning models.
Sound modeling knowledge, including evaluation metrics, model behaviour, drift andperformance interpretation
Experience building production scoring pipelines and monitoring model operations
Familiarity with model versioning and lifecycle-management tools
Experience with CI/CD, automated testing and dependency management
Ability to troubleshoot issues across data pipelines, model execution and deploymentenvironments
Working knowledge of the banking domain and the governance requirements associated withproduction models

Preferred Skills

Experience with Databricks and Azure-based deployment environments
Familiarity with APIs, containers and orchestration platforms
Experience supporting model approvals, audit documentation and controlled releases