Data Scientist+ Cloud | 4+ Yrs | PAN India

Job Title: Data Scientist +Cloud Department: Public Service Data & AI – Growth Network Location: Bangalore, Hyderabad, Chennai, Mumbai, Pune, Gurugram, Kolkata Level: Consultant Experience: 5-7 years Job Summary We are seeking an experienced Data Scientist with strong hands-on experience in Machine Learning, Generative AI, and AWS services. The ideal candidate should be able to translate business problems into data science solutions, develop and deploy AI/ML models, and work with AWS-based data and AI services.

Data Science & AI/ML Development · Analyze large and complex datasets to identify patterns, insights, and business opportunities. · Design, develop, test, and optimize machine learning and statistical models. · Build solutions across areas such as classification, prediction, forecasting, anomaly detection, NLP, and Generative AI. · Perform data exploration, feature engineering, model selection, validation, and performance evaluation. · Develop POCs and MVPs to demonstrate the feasibility and business value of AI/ML solutions. · Support deployment, monitoring, and continuous improvement of models in production environments. AWS Data & AI Solutions · Design and develop data science and AI solutions using AWS services. · Work with services such as Amazon SageMaker, Bedrock, S3, Lambda, Glue, Athena, Redshift, Step Functions, and related AWS AI/ML services. · Build and integrate scalable ML and GenAI workflows on AWS. · Work with data engineering and cloud teams to integrate models with enterprise data platforms and applications. · Apply AWS best practices for security, scalability, performance, and cost optimization. Generative AI · Develop GenAI solutions using LLMs, RAG, embeddings, vector databases, and prompt engineering. · Build and evaluate AI assistants, agents, and knowledge-based applications. · Work with foundation models through Amazon Bedrock or similar platforms. · Evaluate GenAI solutions for accuracy, reliability, performance, and responsible AI considerations. Client Engagement & Solutioning · Work directly with client stakeholders to understand business problems and translate them into data science use cases. · Conduct

discussions, workshops, technical sessions, and solution demonstrations. · Clearly communicate analytical findings and model outputs to both technical and non-technical stakeholders. · Contribute to solution architecture, estimation, proposals, and technical presentations. · Collaborate with cross-functional teams including data engineers, cloud architects, analysts, and application teams.