Data Scientist (12 / 10 / 2025)

Location : Hyderabad and Gurgaon.

Overview

Data Science Team works in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML / AI projects using big analytics toolsets in a CI / CD environment. Analytics toolsets may include DS tools / Spark / Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Azure Pipelines.

You will be part of a collaborative interdisciplinary team around data, where you will be responsible of our continuous delivery of statistical / ML models. You will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments.

Responsibilities

• Delivery of key Advanced Analytics / Data Science projects within time and budget, particularly around DevOps / MLOps and Machine Learning models in scope
• Active contributor to code & development in projects and services
• Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption.
• Partner with ML engineers working on industrialization.
• Communicate with business stakeholders in the process of service design, training and knowledge transfer.
• Support large-scale experimentation and build data-driven models.
• Refine requirements into modelling problems.
• Influence product teams through data-based recommendations.
• Research in state-of-the-art methodologies.
• Create documentation for learnings and knowledge transfer.
• Create reusable packages or libraries.
• Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards
• Leverage big data technologies to help process data and build scaled data pipelines (batch to real time)
• Implement end-to-end ML lifecycle with Azure Databricks and Azure Pipelines
• Automate ML models deployments

Qualifications