Data Scientist
Posted Updated
Description
<p>Job Description – Data Scientist | GenAI & Agentic AI</p><p>Position: Data Scientist</p><p>Experience: 4–8 Years</p><p>Location: Chennai</p><p>Work Mode: Work from Office</p><p><br /></p><p>Job Summary</p><p>We are looking for a skilled Data Scientist with a strong foundation in Machine Learning, Statistical Analysis, and Data-Driven Problem Solving, along with hands-on experience in Generative AI and Agentic AI development.</p><p><br /></p><p>The ideal candidate will have experience building and deploying LLM-powered applications and should be comfortable working with Prompt Engineering, Retrieval-Augmented Generation (RAG), Embeddings, Vector Databases, Tool/Function Calling, and Multi-Agent/Agentic Workflows.</p><p><br /></p><p>This role requires someone who can combine strong traditional Data Science expertise with modern GenAI capabilities to design, develop, evaluate, and deploy AI solutions from experimentation through production.</p><p><br /></p><p>Key Responsibilities</p><p>Develop and implement machine learning and statistical models to solve business problems.</p><p>Design and build Generative AI applications using Large Language Models (LLMs).</p><p>Develop RAG-based solutions using embeddings, vector databases, document retrieval, and contextual generation.</p><p>Implement effective prompt engineering strategies for LLM-based applications.</p><p>Build AI agents and multi-step agentic workflows using tool/function calling and orchestration frameworks.</p><p>Integrate LLM applications with enterprise data sources, APIs, databases, and existing business applications.</p><p>Design and implement scalable AI/ML solutions suitable for production environments.</p><p>Develop evaluation frameworks to assess LLM accuracy, relevance, reliability, latency, and overall application performance.</p><p>Implement appropriate AI guardrails, validation mechanisms, and responsible AI practices.</p><p>Perform data analysis, feature engineering, model development, validation, and optimization.</p><p>Collaborate with engineering, product, and business teams to translate requirements into data and AI solutions.</p><p>Troubleshoot and optimize AI/ML applications for performance, scalability, cost, and reliability.</p><p>Contribute to the deployment, monitoring, and continuous improvement of AI solutions in production.</p><p><br /></p><p>Required Skills</p><p>Data Science & Machine Learning</p><p>Strong understanding of Machine Learning concepts and algorithms.</p><p>Strong foundation in Statistics, Probability, Data Analysis, and Predictive Modeling.</p><p>Hands-on experience with Python and relevant Data Science/ML libraries.</p><p>Experience with data preprocessing, feature engineering, model evaluation, and optimization.</p><p>Good understanding of supervised and unsupervised learning techniques.</p><p><br /></p><p>Generative AI & LLM</p><p>Hands-on experience working with Generative AI and Large Language Models (LLMs).</p><p>Strong understanding of Prompt Engineering and LLM application development.</p><p>Practical experience with RAG (Retrieval-Augmented Generation).</p><p>Experience with Embeddings and Vector Databases.</p><p>Experience implementing Tool/Function Calling.</p><p>Understanding of LLM evaluation, hallucination mitigation, guardrails, and response validation.</p><p><br /></p><p>Agentic AI</p><p>Experience designing and developing AI agents and agentic workflows.</p><p>Understanding of multi-step reasoning and workflow orchestration.</p><p>Experience integrating agents with APIs, enterprise systems, databases, and external tools.</p><p>Familiarity with agent orchestration frameworks is an advantage.</p><p>Deployment & Integration</p><p>Experience taking AI/ML solutions from prototype to production.</p><p>Understanding of APIs, microservices, cloud platforms, and application integration.</p><p>Knowledge of MLOps/LLMOps, monitoring, scalability, and production deployment is preferred.</p><p>Experience working with enterprise data sources and integrating AI solutions into existing applications.</p><p><br /></p><p>Preferred Qualifications</p><p>Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.</p><p>4–8 years of relevant experience in Data Science, Machine Learning, AI, or related areas.</p><p>Experience working on end-to-end AI/ML projects.</p><p>Exposure to cloud platforms such as AWS, Azure, or GCP.</p><p>Familiarity with modern GenAI/LLM frameworks and AI development tools.</p><p>Strong analytical, problem-solving, communication, and collaboration skills.</p>