Lead Data Scientist — GenAI
Global Retail Major · Posted 1 day ago
Location
Bengaluru
Work mode
Hybrid
Type
Full-time
Experience
7 – 12 yrs
Compensation
₹40 – 60 LPA
Posted
1 day ago
A global retail organisation is building a GenAI capability that spans merchandising, marketing, and customer operations. This role leads the platform side — the models, evaluation harness, and MLOps that everything else builds on.
You will define the roadmap alongside the VP of Data and manage a growing team of applied scientists and ML engineers.
Own the LLM platform strategy — model selection, fine-tuning, evaluation
Build and maintain the shared prompt/agent framework used across business teams
Lead a team of 4–6 applied scientists + ML engineers
Set the evaluation harness — offline + online, safety + performance
Represent the platform in enterprise architecture reviews
7+ years in data science / ML with 2+ leading a team
Deep hands-on GenAI experience — LLMs, RAG, agents, evals
PyTorch fluency + production MLOps (Ray, Kubeflow, or equivalent)
Vector database experience (pgvector / Pinecone / Weaviate)
Track record of shipping ML systems to production
Published research or open-source ML contributions
Experience in retail / e-commerce data
Fine-tuning open-weight models (Llama, Mistral)
Top-quartile compensation for GenAI leadership in Bengaluru
Compute budget for research and evaluation
Direct executive sponsorship and roadmap authority
Direct recruiter and hiring-manager access — no black-hole applications
Structured, timely feedback after every stage
Honest guidance on compensation, notice period, and market
Onboarding support in the first 30 days after joining
Structured, timely, and short.
- 01
Recruiter screen (30 min)
- 02
Technical + case discussion (90 min)
- 03
Leadership panel (60 min)
- 04
Executive conversation with VP Data (45 min)
Other Data & AI openings.
Hire smarter, build faster, scale further — with one partner.
Book a 30-minute consultation with our enterprise team. We'll send a tailored proposal — costs, capacity, milestones — within 48 hours.
