Data Scientist

Data Scientist

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MISSION:

The GenAI Data Scientist designs, builds, evaluates, and deploys Generative AI solutions, with strong focus on GenAI agents and agentic workflows.

He/she is responsible for:

Understanding business needs and converting them into GenAI agent use cases

Building GenAI agents using LangGraph or similar agentic frameworks

Designing workflows with tool calling, routing, memory, state management, guardrails, and human escalation

Connecting agents with enterprise data, APIs, databases, applications, and automation tools

Building and optimizing RAG knowledge stores when knowledge retrieval is required

Developing clean, modular, scalable, and deployment-ready Python code

Evaluating agents for accuracy, reliability, hallucination risk, latency, cost, and user experience

Working with data, platform, and software engineering teams to move GenAI solutions to production

KEY EXPECTED ACHIEVEMENTS:

Business need is translated into a clear GenAI agent solution

Agent architecture, workflow, tools, memory, prompts, and guardrails are designed and documented

Agentic workflows are built, tested, and optimized using LangGraph or similar frameworks

RAG knowledge stores are implemented and optimized when required

Python code is modular, testable, maintainable, and production-ready

The solution is deployed with logging, monitoring, error handling, access control, and cost control

Results, limitations, risks, and usage guidelines are clearly presented to business and technical stakeholders

Source code, prompts, configuration, and documentation are delivered

Peer reviews are organized to ensure quality, scalability, and reliability