Associate MLOps Analyst

Job Description

Alimentation Couche-Tard Inc., (ACT) is a global Fortune 200 company and a leader in the convenience store and fuel space with over 16,700 stores. It has footprints across 31 countries and territories. Circle K India Data & Analytics team is an integral part of ACT's Global Data & Analytics Team, and the Associate ML Ops Analyst will be a key player on this team that will help grow analytics globally at ACT.

The hired candidate will partner with multiple departments, including Global Marketing, Merchandising, Global Technology, and Business Units.

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Location: Cyber Hub, Gurugram, Haryana (5 days in office)

Job Type: Permanent, Full-Time (40 Hours)

Reports To: Senior Manager Data Science

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About The Role

The incumbent will be responsible for implementing Azure data services to deliver scalable and sustainable solutions, build model deployment and monitor pipelines to meet business needs.

Roles & Responsibilities

Development and Integration

• Collaborate with data scientists to deploy ML models into production environments
• Implement and maintain CI/CD pipelines for machine learning workflows
• Use version control tools (e.g., Git) and ML lifecycle management tools (e.g., MLflow) for model tracking, versioning, and management.
• Design, build as well as optimize applications containerization and orchestration with Docker and Kubernetes and cloud platforms like AWS or Azure
  
  

Automation & Monitoring

• Automating pipelines using understanding of Apache Spark and ETL tools like Informatica PowerCenter, Informatica BDM or DEI, Stream Sets and Apache Airflow
• Implement model monitoring and alerting systems to track model performance, accuracy, and data drift in production environments.
  
  

Collaboration and Communication

• Work closely with data scientists to ensure that models are production-ready
• Collaborate with Data Engineering and Tech teams to ensure infrastructure is optimized for scaling ML applications.
  
  

Optimization and Scaling

• Optimize ML pipelines for performance and cost-effectiveness
  
  

Operational Excellence

• Help the Data teams leverage best practices to implement Enterprise level solutions.
• Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project
• Helping to define common coding standards and model monitoring performance best practices
• Continuously evaluate the latest packages and frameworks in the ML ecosystem
• Build automated model deployment data engineering pipelines from plain Python/PySpark mode
  
  

Stakeholder Engagement

• Collaborate with Data Scientists, Data Engineers, cloud platform and application engineers to create and implement cloud policies and governance for ML model life cycle.
  
  

Job Requirements

Education & Relevant Experience

• Bachelor's degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)
• Master's degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.)
• 1-2 years of relevant working experience in MLOps
  
  

Behavioural Skills

• Delivery Excellence
• Business disposition
• Social intelligence
• Innovation and agility
  
  

Knowledge

• Knowledge of core computer science concepts such as common data structures and algorithms, OOPs
• Programming languages (R, Python, PySpark, etc.)
• Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.)
• Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools
• Exposure to ETL tools and version controlling
• Experience in building and maintaining CI/CD pipelines for ML models.
• Understanding of machine-learning, information retrieval or recommendation systems
• Familiarity with DevOps tools (Docker, Kubernetes, Jenkins, GitLab).