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 environmentsImplement and maintain CI/CD pipelines for machine learning workflowsUse 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-readyCollaborate 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 projectHelping to define common coding standards and model monitoring performance best practices Continuously evaluate the latest packages and frameworks in the ML ecosystemBuild 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).

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