Pune, Maharashtra, India
Information Technology
Full-Time
IndiGo (InterGlobe Aviation Ltd)
Overview
Job Summary
We are looking for a skilled and motivated Data Scientist to join our team as an individual contributor. The ideal candidate should have at least two years of experience in data science or ML engineering, with hands-on expertise in Databricks, PySpark, and SQL. You’ll be responsible for owning and delivering scalable machine learning solutions end-to-end—from exploration to production—working independently and collaborating closely with business and engineering teams.
Key Responsibilities
We are looking for a skilled and motivated Data Scientist to join our team as an individual contributor. The ideal candidate should have at least two years of experience in data science or ML engineering, with hands-on expertise in Databricks, PySpark, and SQL. You’ll be responsible for owning and delivering scalable machine learning solutions end-to-end—from exploration to production—working independently and collaborating closely with business and engineering teams.
Key Responsibilities
- Own and deliver the complete lifecycle of machine learning projects, from data exploration and feature engineering to model deployment and monitoring.
- Develop, optimize, and maintain ML and DL models using scalable tools and frameworks.
- Build and maintain robust MLOps pipelines for model versioning, testing, deployment, and retraining.
- Work extensively on Databricks, leveraging PySpark, MLflow, and SQL to build production-grade ML pipelines.
- Automate and monitor workflows for data preparation, model training, and model performance tracking.
- Integrate ML solutions with business systems and APIs for real-time or batch inference.
- Collaborate with data engineers, product managers, and domain experts to translate business problems into ML solutions.
- Bachelor’s or master’s degree in Computer Science, Data Science, or a related field from top-tier institutions.
- 2+ years of experience as an ML Engineer, Data Scientist, or in a similar technical role.
- Demonstrated experience deploying at least one end-to-end ML pipeline into production.
- Strong command of Databricks, PySpark, and SQL for large-scale data processing.
- Proficiency with Python and familiarity with MLOps tools like MLflow, Airflow, or Kubeflow.
- Hands-on experience with cloud platforms (Azure preferred; AWS or GCP acceptable).
- Solid understanding of machine learning and deep learning techniques, as well as EDA and data wrangling.
- Familiarity with CI/CD, Docker, Kubernetes, and version control (Git).
- Self-driven, highly organized, and capable of working independently with minimal supervision.
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