Data Scientist, Technical Lead- Bangalore

Prodapt Solutions; Bengaluru; On-site; INR 1,500,000 - 2,600,000; Full time

Job summary

Prodapt Solutions in Bengaluru seeks an experienced Data Scientist to build, validate, and deploy advanced ML and GenAI solutions. You will develop enterprise GenAI apps, leverage RAG and LLMs, and design multi-step AI agents with robust human-in-the-loop controls.

Ideal candidates have 5+ years of DS/ML, strong Python/SQL skills, and experience with GenAI frameworks, REST APIs, and cloud deployment practices. Hybrid collaboration across teams is expected.

Qualifications

• 5+ years of hands-on Data Science and ML experience with end-to-end model deployment.
• GenAI experience (1+ years) including RAG and LLM application development.
• Strong Python, SQL, pandas, NumPy, and scikit-learn skills.
• Experience with at least one GenAI framework (LangChain, LlamaIndex, LangGraph, or equivalent).
• Familiarity with REST APIs, cloud environments, and ML deployment practices.

Responsibilities

• Build and validate predictive models (classification, regression, forecasting) and operationalize them via scalable pipelines.
• Develop enterprise GenAI apps using LLMs, embeddings, RAG, and vector search with attention to accuracy and cost.
• Create tool-enabled AI agents using LangGraph, CrewAI, or Google ADK with human-in-the-loop controls.
• Take solutions from experimentation to production, covering APIs, versioning, monitoring, CI/CD, and cloud AI platforms.
• Translate business needs into measurable AI use cases and clearly communicate results and limitations.

Skills

Python programming

GenAI experience

REST APIs & cloud

DS/ML end-to-end

LLM + RAG

Education

Bachelor's or Master's in a quantitative discipline

Tools

LangChain

LlamaIndex

LangGraph

Job description

Role & responsibilities :-

• Data Science & ML: Build and validate predictive models (classification, regression, clustering, forecasting, anomaly detection) and operationalize them through scalable pipelines.
• Generative AI: Develop enterprise GenAI applications using leading LLMs, implementing RAG, embeddings, vector search, and prompt engineering, with attention to accuracy, groundedness, and cost.
• Agentic AI (strong advantage): Build tool-enabled, multi-step AI agents using frameworks such as LangGraph, CrewAI, or Google ADK, with human-in-the-loop controls and reliability monitoring.
• MLOps / LLMOps: Move solutions from experimentation to production, covering APIs, versioning, monitoring, CI/CD, and cloud AI platforms (AWS Bedrock, Azure AI Foundry, Google Vertex AI).
• Stakeholder Engagement: Translate business needs into measurable AI use cases and communicate results and limitations clearly to technical and non-technical audiences.

Key Requirements

• 5+ years of hands-on Data Science and ML experience, including end-to-end model deployment
• Practical GenAI experience (1+ years preferred), including RAG and LLM application development
• Strong Python, SQL, pandas, NumPy, and scikit-learn skills
• Experience with at least one GenAI framework (LangChain, LlamaIndex, LangGraph, or equivalent)
• Familiarity with REST APIs, cloud environments, and ML deployment practices
• Bachelors or Masters degree in a quantitative discipline

Preferred Qualifications

• Agentic AI development experience and familiarity with MCP or similar integration patterns
• Exposure to fine-tuning and cost-efficient LLM inference
• Understanding of AI guardrails, evaluation frameworks, and responsible AI practices
• Telecom industry experience, particularly in churn, billing, network analytics, or customer experience

Ideal Candidate

A hands-on data scientist with strong ML foundations, proven GenAI and RAG delivery experience, a production engineering mindset, and the ability to adapt to new business domains.