JD - Data Scientist - Experience: 3-5 years

Skills

• Working understanding of Agentic AI concepts such as autonomous agents, goal-driven reasoning, planning, memory, and tool usage.
• Hands-on experience or exposure to building single-agent solutions and contributing to multi-agent workflows for decision support and workflow automation.
• Experience developing AI agents that can perform reasoning, action execution, and outcome evaluation, with basic feedback or retry mechanisms.
• Practical experience using agent frameworks such as LangChain, LangGraph, AutoGen, CrewAI.
• Ability to integrate LLMs with APIs, tools, databases, and internal systems.
• Hands-on experience with prompt engineering, prompt chaining, tool/function calling, and structured agent workflows.
• Understanding of agent memory concepts, including short-term context handling, embeddings, and basic usage of vector databases.
• Exposure to implementing basic guardrails, logging, monitoring, and evaluation for AI or agentic systems, with awareness of enterprise governance needs.
• Good understanding of Responsible AI principles, including safety, data privacy, hallucination awareness, and human-in-the-loop approaches.

Business & Delivery Skills

• Ability to understand business needs and map them to data-driven and AI-based technical solutions.
• Hands-on experience working in Agile project delivery environments.
• Ability to conceptualize and visualize end-to-end business solutions at both high-level and detailed levels.
• Strong articulation skills to translate business requirements into technical designs and AI solutions.
• Good analytical and problem-solving skills.
• Strong communication, listening, and probing skills.
• Good interpersonal skills and ability to collaborate effectively within cross-functional teams.

Roles & Responsibilities

• Understand business problems and contribute to the development of impactful, data-driven and AI-driven solutions.
• Design, develop, and support deployment of statistical, machine learning, deep learning, and agent-based AI solutions under senior guidance.
• Build factual, predictive, and AI-driven models to address business challenges.
• Identify relevant data sources, assess data accessibility, and assist in data augmentation and enrichment strategies.
• Develop meaningful data visualizations using tools such as D3.js, Dash, and Plotly.

Internal

Internal

• Contribute to the implementation of agentic AI solutions that support business workflows and decision processes.
• Collaborate with business stakeholders, architects, and engineering teams to deliver scalable and reliable AI solutions.
• Follow established practices to ensure performance, reliability, security, and governance of AI solutions in enterprise environments.