Associate MLOps Analyst

Circle K

Gurugram District

On-site

INR 500,000 - 800,000

Full time

14 days+

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Job summary

Circle K is seeking an Associate ML Ops Analyst to join their Data & Analytics team in Gurugram. The role involves deploying machine learning models, implementing CI/CD pipelines, and optimizing scalable solutions to meet business needs. A Bachelor’s degree in a quantitative field is required, with preference for candidates holding a Master’s degree. Candidates should have knowledge of Python, Azure, and experience with tools like Docker and Apache Spark to succeed in this dynamic environment. Join us at Circle K to contribute to our analytics growth across global markets.

Qualifications

Experience in MLOps with 1-2 years of relevant working experience.
Knowledge of core computer science concepts such as common data structures and algorithms, OOPs.
Understanding of machine-learning, information retrieval, or recommendation systems.

Responsibilities

Deploy ML models into production environments.
Implement and maintain CI/CD pipelines for machine learning workflows.
Collaborate with Data Engineers and Tech teams to ensure infrastructure is optimized for scaling ML applications.
Monitor model performance, accuracy, and data drift in production environments.

Skills

Machine Learning

CI/CD Pipelines

Python

Azure

Docker

Kubernetes

Apache Spark

ETL

Education

Bachelor’s degree in Statistics, Business Analytics, Data Science, Math, Economics

Master’s degree in MBA/MS Computer Science/M.Tech Computer Science

Tools

Git

Informatica PowerCenter

Apache Airflow

MLflow

AWS

GCP

Job description

Direct message the job poster from Circle K

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.

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).

Seniority level