Data Scientist, Lead- Bangalore

Prodapt Solutions; Bengaluru; Hybrid; INR 1,200,000 - 2,000,000; Full time

Job summary

Prodapt Solutions in Bengaluru seeks a hands-on data scientist with GenAI and ML expertise to build production-grade AI solutions. You will develop predictive models, implement RAG, embeddings, and agentic workflows, and collaborate with stakeholders to translate business needs into measurable AI use cases.

Strong Python/SQL skills and experience with GenAI frameworks and cloud deployment are required. The ideal candidate thrives in a fast-paced tech environment and communicates clearly with

Qualifications

• 5+ years of hands-on Data Science and ML experience, including end-to-end model deployment.
• Practical 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).
• Familiarity with REST APIs, cloud environments, and ML deployment practices.
• Bachelor's or Master's degree in a quantitative discipline.

Responsibilities

• Build and validate predictive models (classification, regression, clustering, forecasting, anomaly detection).
• Develop enterprise GenAI applications using leading LLMs with RAG, embeddings, vector search, and prompts.
• Create multi-step AI agents using frameworks like LangGraph, CrewAI, or Google ADK with human-in-the-loop controls.
• Move solutions from experimentation to production, covering APIs, versioning, monitoring, CI/CD, and cloud AI platforms.
• Translate business needs into measurable AI use cases and communicate results clearly to technical and non-technical audiences.

Skills

Python

SQL

pandas

NumPy

scikit-learn

Education

Bachelor's or Master's degree in a quantitative discipline

Tools

LangChain

LlamaIndex

LangGraph

Job description

Key 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.