Data Scientist + Cloud exp || 4+ Years || Location: Bangalore, Hyderabad, Chennai, Mumbai, Pune, Gurugram, Kolkata

Job Qualifications:

[Btech/MBA mandatory]

Data Science + Cloud experience mandatory

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.

The role requires a combination of strong data science fundamentals, hands-on technical capabilities, and client-facing skills, with the ability to work closely with business stakeholders, data engineers, architects, and AI teams.

Key Responsibilities

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 requirements 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.

Required Qualifications

• Bachelor's/Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
• 5-7+ years of hands-on experience in Data Science, Machine Learning, or AI.
• Strong programming skills in Python and experience with common data science and ML libraries.
• Hands-on experience developing and deploying machine learning models.
• Practical experience with AWS cloud services, particularly AWS data and AI/ML services.
• Experience with Amazon SageMaker and/or Amazon Bedrock is strongly preferred.
• Good understanding of supervised and unsupervised learning, statistical modelling, feature engineering, and model evaluation.
• Experience working with SQL and large datasets.
• Exposure to Generative AI, LLMs, RAG, prompt engineering, and vector databases.
• Understanding of MLOps, model deployment, monitoring, and CI/CD concepts.
• Strong analytical, problem-solving, and communication skills.
• Experience working in client-facing or consulting environments is preferred.

Preferred Skills

• AWS certifications related to Machine Learning, Data, or Cloud.
• Experience building production-grade AI/ML solutions on AWS.
• Experience with NLP, document intelligence, predictive analytics, or fraud/anomaly detection use cases.
• Familiarity with responsible AI, model governance, and data privacy principles.
• Experience in Public Service or Government projects would be an advantage.