Data Scientist AIML

Job description

- 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 emerging AI/ML techniques