AI Data Scientist

• Explore, clean, and analyse large, complex datasets to uncover patterns, trends, and opportunities that drive actionable insights.
• Develop, train, and validate machine learning, statistical, and predictive models that solve real business problems and deliver measurable impact.
• Design and run experiments (A/B tests, hypothesis tests, simulations) to evaluate ideas, quantify outcomes, and guide decisionmaking.
• Collaborate with data engineers, analysts, product managers, and domain experts to translate business requirements into welldefined modelling tasks.
• Build endtoend ML pipelinesfrom feature engineering and preprocessing to deploymentready model outputs.
• Apply advanced techniques such as NLP, timeseries forecasting, anomaly detection, optimisation, or LLM/GenAI methods where relevant.
• Implement model evaluation frameworks using offline metrics, crossvalidation, online experiments, and humanintheloop feedback loops.
• Communicate insights clearly through dashboards, visualisations, written summaries, and presentations tailored to technical and nontechnical stakeholders.
• Ensure models are interpretable and explainable where required, providing transparency into key drivers and assumptions.
• Work with engineering teams to deploy models into production, monitor performance, and retrain or recalibrate as data and conditions change.

Your Profile

Essential skills/knowledge/experience: (Up to 10, Avoid repetition)

Role- Data Scientist ( 5 to 12 Yrs )

• Hands-on experience with GenAI, Gemini or Open source LLMs and develop GenAI applications for Code Translation, Text Extraction, Summarisation and SDLC Optimization etc.
• Hands-on Experience with AI Agents, Chat bots, RAG (Retrieval-Augmented Generation), and vector databases. ( PG vector / croma DB )
• Hands-on Experience with GenAI Performance Evaluation tools like Pegasus, Ragas, DeepEval
• Create Conversational Interface with React JS or other Frontend components, Develop and deploy AI agents using LangGraph and ADK, A2A, MCP
• Strong programming skills in Python (experience with LangChain/LangGraph / LangSmith frameworks) and TypeScript ( preferable )
• Solid understanding of LLMs, prompt engineering, and graph-based workflows.
• Knowledge and implementation of Input and Output guardrails in addressing Hallucination, PII filtering, HAP and Bias etc.
• Implemented security best practices, Experience to address spikes and Denial of wallet attacks, DDoS attack and other Spike arrest strategies
• Knowledge of API Gateways and ISTIO , ability to Diagnose and intercept failures in End to End communication
• Hands-on Experience with API Development and Microservices architecture

Desirable skills/knowledge/experience: (As applicable)

• Strong experience applying machine learning, statistical modelling, and predictive analytics to realworld business problems.
• Collaborate with cross-functional teams to ability to resolve end to end connectivity and Data Integrations
• Experience working with large, complex datasets, including data cleaning, feature engineering, and exploratory data analysis.
• Familiarity with LLMs, NLP techniques, and GenAI frameworks, including embeddings, prompt engineering, or finetuning.
• Experience building endtoend ML pipelines, including model validation, optimisation, deployment, and monitoring.
• Understanding of MLOps practices, including model versioning, model registries, CI/CD for ML, and automated training/inference workflows.
• Ability to translate business problems into analytical tasks and communicate insights in a clear, concise manner to technical and nontechnical audiences.
• Knowledge of data governance, including data quality, lineage, ethics, privacy considerations, and responsible AI principles.
• Comfort working with cloud platforms (GCP preferred) for model training, deployment, and scalable compute.

A growthoriented mindset with enthusiasm for exploring new algorithms, tools, and e