Lead Data Scientist
1 day ago
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, ₹4,800,000.00 per year
Work Location: In person
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