Lead Data Scientist

SIM DIGITAL SERVICES; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

SIM DIGITAL SERVICES is looking for a Lead Data Scientist for their Bengaluru office. In this hands-on role, you will lead R&D projects in conversational AI, establish benchmarks, and build AI systems ready for production. The ideal candidate will hold an advanced degree in a relevant field and have over five years of industry experience, particularly in NLP and machine learning. Benefits include a dynamic work environment with opportunities for mentorship and innovation in AI technologies.

Qualifications

• 5+ years of hands-on experience in data science, at least 3 years focused on NLP.
• Deep, hands-on experience with the modern LLM stack.
• Experience with model fine-tuning using Hugging Face and PEFT techniques.

Responsibilities

• Lead R&D projects in LLMs and conversational AI.
• Design and maintain evaluation frameworks for AI models.
• Own strategy for proprietary and open-source model usage.
• Mentor junior scientists and engineers.

Skills

LLM stack experience

NLP and Machine Learning

Python proficiency

RAG pipeline optimization

Experimentation and problem-solving

Education

Bachelor's, MS, or PhD in Computer Science, AI, NLP, or related field

Tools

PyTorch

Hugging Face

LangChain

Vector databases

Job description

Overview

The Lead Data Scientist is a critical, hands-on role at the heart of our platform's intelligence. You will be our senior expert on the "science" of conversational AI, responsible for researching, developing, and refining the core LLM-powered systems that our agents rely on. This is a "player-coach" role for a seasoned expert who is passionate about pushing the boundaries of what's possible with LLMs. You will lead our applied research and development efforts, establish new benchmarks for model performance, and pioneer novel techniques for agent-based systems. You will collaborate closely with Product and Engineering to translate your breakthroughs into tangible, production-ready features that define the next generation of our platform.

Responsibilities

• Lead R& D projects to explore, prototype, and implement cutting-edge techniques in LLMs and conversational AI.
• Focus areas include advanced RAG strategies, model fine-tuning, agentic workflows, multi-agent orchestration, and prompt optimization.
• Stay constantly apprised of the latest academic research (e. g., from ACL, NeurIPS, and EMNLP) and apply relevant findings to our platform.
• Design, build, and maintain a robust evaluation framework to rigorously benchmark our AI models and agent performance against internal and external standards.
• Define key metrics for quality, accuracy, latency, cost, and safety.
• Analyze model failure modes in-depth and develop strategies for continuous improvement.
• Own the strategy for our model stack, including when to use proprietary models (e. g., GPT-4o, Claude 3), open-source models, or fine-tuned specialist models.
• Conduct experiments and lead initiatives for fine-tuning or (P)EFT-tuning models for specific customer domains and tasks.
• Act as the primary technical consultant to the Product team on AI/LLM capabilities, helping to define a feasible and ambitious product roadmap.
• Partner with Engineering to develop MLOps pipelines for deploying, monitoring, and updating models and AI systems in production.
• Provide deep technical guidance and mentorship to our Forward Deployed Engineering team on complex AI challenges.
• Mentor junior data scientists and engineers on the team, fostering a culture of scientific rigor and innovation.
• Act as ConvoZen AI's internal and external subject matter expert on data science for generative AI.

Requirements

• Bachelor's, MS, or PhD in Computer Science, AI, NLP, Machine Learning, or a related quantitative field.
• 5+ years of hands-on industry experience in data science, with at least 3+ years focused specifically on NLP and machine learning.
• Demonstrable, deep, hands-on experience with the modern LLM stack.

You Must Have

• Experience building and optimizing complex RAG (Retrieval-Augmented Generation) pipelines.
• Practical experience with model fine-tuning (e. g., using Hugging Face, Axolotl) and parameter-efficient tuning (PEFT) techniques.
• Deep understanding of agentic frameworks (e. g., LangChain, LlamaIndex) and the principles of tool use and multi-step reasoning.
• A strong grasp of core NLP concepts, including transformers, embeddings, tokenization, and dialogue systems.
• Expert-level proficiency in Python.
• Deep experience with modern ML/NLP libraries (e. g., PyTorch, Hugging Face transformers, datasets, evaluate, and LangChain).
• Experience with vector databases (e. g., Pinecone, Weaviate, Milvus).
• A proven ability to run structured experiments, work with ambiguity, and translate complex research into practical, high-impact solutions.

Bonus Points

• A strong record of publications in top-tier AI, ML, or NLP conferences (e. g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL).
• Experience building and deploying AI models in a production, low-latency environment (MLOps).
• Experience with multi-modal models (text, image, audio).
• Experience leading small project teams or mentoring junior data scientists.