Data Scientist - Analyst

Role- Data Scientist Skill-Data Scientist, Python, Advanced SQL, GCP, Vertex AI, BigQuery ML, Cloud Functions, MLOps, Kubeflow, TensorFlow, PyTorch Location- Bangalore, Hyderabad Shift Timing- 4pm-1am Work Model- Hybrid(3 Days WFO & 2 Days WFH) About Omnicom Global Solutions Omnicom Global Solutions (OGS) is an integral part of Omnicom Group, a leading global marketing and corporate communications company. Omnicom’s branded networks and specialty firms deliver advertising, strategic media planning and buying, digital and interactive marketing, direct and promotional marketing, public relations, and other specialized communication solutions to over 5,000 clients across more than 70 countries. OGS India serves as a key global capability center for Omnicom, enabling its agencies and group companies with scaled delivery, specialized expertise, and integrated solutions. Our capabilities span Media, Data & Analytics, Technology, MarTech, Commerce, Business Support Solutions, Creative Production, Healthcare, and Strategy & Insights. With a workforce of over 7,000 professionals in India, OGS continues to expand its capabilities and global impact, supporting the evolving needs of clients and agencies. We are committed to building future-ready talent and delivering high-quality, outcome-driven solutions.

Model Development: Design, build, train, and evaluate predictive models and machine learning algorithms using Python, TensorFlow, and PyTorch.

Data Engineering & Querying: Extract, transform, and analyze large datasets using Advanced SQL and BigQuery / BigQuery ML.

GCP Architecture: Leverage Google Cloud Platform services (Vertex AI, Cloud Functions, BigQuery) to build production-grade ML pipelines.

MLOps & Automation: Build and maintain automated end-to-end ML pipelines using Kubeflow and Vertex AI for continuous integration, training, deployment, and monitoring (CI/CD/CT).

Serverless Workflows: Write and deploy serverless code using Cloud Functions to trigger ML pipelines and handle event-driven data processing.

Cross-Functional Collaboration: Partner with data engineers, software developers, and business stakeholders to integrate ML solutions into existing applications Qualifications Required Skills & Qualifications Experience: 3–5 years of relevant experience as a Data Scientist or Machine Learning Engineer.

Core Programming: Advanced proficiency in Python and deep knowledge of data manipulation libraries (Pandas, NumPy, Scikit-learn).

Database & SQL: Strong expertise in Advanced SQL (complex joins, window functions, query optimization) and experience working with BigQuery / BigQuery ML.

Cloud Platform: Proven hands-on experience with Google Cloud Platform (GCP), specifically Vertex AI and Cloud Functions.

ML Frameworks: In-depth experience with TensorFlow and/or PyTorch.

MLOps & Pipeline Tools: Practical experience using Kubeflow to orchestrate machine learning workflows and manage model lifecycles in production.

Problem-Solving: Strong analytical and algorithmic skills with a track record of deploying robust ML models into live environments.