Job Title:

Data Scientist Classical ML, SHAP & GenAI / RAG Pipelines (100% Remote)

Role Category:

Data Science & Analytics / Machine Learning

Employment Type:

Full Time, Permanent

Work Location:

100% Fully Remote

Are you a hands-on Data Scientist with strong roots in Classical Machine Learning, Model Explainability (SHAP), and modern LLM / RAG pipeline development?

At V4C.ai, a high-growth, Databricks-funded partner company scaled to 600+ professionals, we are expanding our core Data Science and AI practices. We are looking for a Data Scientist who brings strong mathematical/statistical rigor in classical ML, transparent expertise in model interpretability (SHAP/XAI), and practical exposure to generative AI workflows (LLMs, RAG).

Key Responsibilities

- Core & Classical ML: Design, train, evaluate, and deploy classical machine learning models (Regression, Classification, Tree-based algorithms, Clustering) for complex enterprise problems.
- Model Explainability (XAI): Leverage SHAP (Shapley Additive exPlanations), LIME, or feature importance frameworks to interpret complex model predictions and communicate insights to stakeholders.
- LLM & RAG Pipelines: Build, optimize, and maintain Retrieval-Augmented Generation (RAG) pipelines using vector databases, embedding models, and LLM frameworks (LangChain / LlamaIndex).
- Data Engineering & Pipelines: Write robust, production-grade Python and SQL code to handle feature engineering, data extraction, and data preparation.
- Collaboration & Innovation:



Partner with enterprise clients and internal engineering teams to deliver scalable, AI-driven solutions across Databricks and cloud ecosystems.

Required Skills & Qualifications

- Experience Level: 2 to 10 years of hands-on data science engineering experience (roles open from Junior/Mid-level up to Senior Data Scientist).
- Core Technical Stack: Strong proficiency in Python (NumPy, Pandas, Scikit-Learn, PyTorch/TensorFlow) and SQL.
- Classical Data Science: Solid foundation in machine learning algorithms, statistical modeling, hypothesis testing, and model evaluation metrics.
- Model Interpretability: Hands-on experience implementing SHAP for model explainability and auditing.
- GenAI / LLM Capabilities: Practical experience or strong understanding of LLMs, RAG architecture, vector stores (e.g., Pinecone, Chroma, FAISS), and prompt engineering.

Why Join V4C.ai?

- 100% Remote Work Setup: Complete flexibility to work from anywhere.
- Databricks-Funded Scale: Work with a fast-growing partner firm backed directly by Databricks, operating at the bleeding edge of enterprise AI.
- Cutting-Edge Tech Stack: Balance core classical ML models with next-gen Claude, LLM, and Lakehouse AI architectures.

How to Apply / Reach Out Directly If you meet the technical bar and are ready to work on enterprise-grade AI & Data Science solutions, reach out directly:

- Email: Send your resume to [email protected] and mention subject as "Data Scientist naukri"
- LinkedIn: Connect and message directly at Ganesh Manoharan on LinkedIn

📌 Data Scientist - Classical ML, SHAP & GenAI/RAG Pipelines (Remote) (Bengaluru)
🏢 V4c Info Systems
📍 Bengaluru