Sr Data Scientist with GCP/Azure/AWS

Long Description

JD – Senior Data Scientist 
Summary:  We are seeking a seasoned Senior Data Scientist with overall 8 yrs and at least 6 years of hands-on experience in developing GenAI/machine learning models and deploying them in a cloud environment, preferably on Google Cloud Platform . The ideal candidate will design microservice-based solutions, containerize deployments  and drive end-to-end SDLC practices. Experience in the pharma domain is a strong advantage.
Total Experience - 8-10 Years
Location - Noida, Pune,Chennai,Pune, Mumbai
Notice -Only Imemdiate Joiner
Key Responsibilities
Lead end-to-end development of GenAI/ML models: problem framing, data preparation, model selection, training, evaluation, and iteration.
Architect and implement microservice-based AI solutions and deploy them in containerized environments 
Incorporate and operationalize defined ML pipelines with MLOps practices: model versioning, feature stores, experiment tracking, CI/CD for ML, monitoring, and rollback strategies.
Ensure cloud security, data governance, and compliance in line with regulatory requirements; manage IAM roles, data access controls, and data lineage.
Collaborate with cross-functional teams data engineers, software engineers, product, regulatory/compliance, analytics) to translate business needs into robust ML solutions.
Uphold SDLC standards: requirements gathering, design, development, testing, deployment, maintenance, and documentation; promote reusable patterns and best practices.
Mentor and guide junior scientists; contribute to code reviews, standards, and knowledge sharing.
Stay current with GenAI advancements and evaluate new tools/approaches; produce reproducible experiments and artifacts.

Required Qualifications
Overall 8 yrs and Minimum 6 years of hands-on experience developing GenAI/ML models and deploying them in a cloud environment.
Proficiency with Google Cloud Platform and its AI/ML offerings Like- Vertex AI BigQuery Dataflow Cloud Storage Cloud Run

Must have experience working with any agentic framework
Knowledge of Retrieval-Augmented Generationconcepts and processes
Strong software engineering skills: Python  experience with ML frameworks and API development
Experience designing and deploying microservices architectures and containerized solutions Docker Kubernetes preference for GKE
Solid experience in MLOps: model versionin experiment automated training feature stores model registries monitoring and governance
Data processing and analytics expertise: SQL, data pipelines, ETL/ELT concepts, data quality, and data visualization support.
Excellent problem-solving, communication, and collaboration skills; ability to work with cross-disciplinary teams.
Understanding of cloud security concepts, IAM, and basic principles of data privacy and compliance.
Demonstrated ability to translate business problems into scalable ML solutions and to communicate technical concepts to non-technical stakeholders.
Preferred Qualifications
Experience in the pharmaceutical/pharma domain or regulated industries; familiarity with GxP, or similar data governance requirements.

Area(s) of responsibility