Lead Data Scientist

Overview

We are seeking a Senior Data Scientist / Lead (7-10 yrs exp) who can architect data-driven solutions, lead ML/AI initiatives, and guide a team working on a mission-critical banking environment.The ideal candidate has deep expertise in Elasticsearch analytics, AIOps, machine learning, agentic AI, and can drive end-to-end model lifecycle and platform integration.

This role requires strong engineering depth and the ability to work across cross-functional teams and customer stakeholders.

Key Responsibilities

Technical Leadership & Architecture

• Architect ML pipelines for high-volume logs/metrics/traces ingested via Elasticsearch & Kafka.• Define standards for data modelling, index strategy, retention, aggregation, and search optimization.• Design end-to-end AI/ML solutions integrated with AIOps workflows and customer operations.

Advanced ML & AIOps

• Build advanced models for:

o Incident prediction & noise reductiono Event correlation & causal clustering

o Predictive capacity planning

o Automated RCA•

Lead design of reinforcement learning or agentic AI systems to automate incident triage.

Agentic AI / LLM Innovation

• Build and deploy agentic AI solutions for:

o Automated RCA assistantso Observability copilots

o Log/metric narrative generation

o Knowledge graph + RAG systems for SRE & Ops intelligence•

Evaluate appropriate foundation models & vector search approaches using Elasticsearch/OpenSearch/similar tools.

Stakeholder Management & Delivery

• Collaborate with architects, SMEs, and client teams to translate requirements into scalable ML solutions.• Lead a small team of DS/ML/DE members; conduct code reviews, mentor, and ensure engineering quality.• Manage project delivery, roadmaps, PoCs, and continuous improvement initiatives.

Required Skills

Technical Expertise

• Deep hands-on experience with Elasticsearch query DSL, aggregations, anomaly detection modules, index management, tuning & scaling.• Strong Kafka experience: stream processing, consumers, producers, and integration with ML pipelines.• Expert-level Python for ML engineering; experience with PyTorch/TensorFlow preferred.• Advanced experience with AIOps ecosystems: Dynatrace, Grafana, Prometheus, Kibana, or similar.• Strong exposure to LLMs, agentic AI, embeddings, vector search, and retrieval pipelines.• Hands-on with designing scalable microservices for inference and automation workflows.• Experience working with distributed systems and performance optimization.

Leadership Skills

• Ability to guide DS/ML teams while still being hands-on.• Strong communication: able to explain complex data concepts to non-technical stakeholders.• Demonstrated experience driving end-to-end delivery in enterprise environments.

Education & Experience

• Bachelor’s/Master’s degree in Computer Science, Data Science or related fields.• 7–10 years of experience in Data Science / ML Engineering.• Prior experience in enterprise-scale environments (Banking/NBFC/Telecom preferred).

Job Type: Full-time

Pay: ₹3,600,000.00 - ₹4,800,000.00 per year

Work Location: In person