Build and scale ML engineering and data engineering functions.
Establish MLOps frameworks for standardized, production-grade model development and monitoring.
Ensure smooth model transition from data science experimentation to live deployment.
• Enterprise Decisioning Platform
Design and operationalize a centralized decisioning platform that integrates low-code model development, AutoML, rule engines, and workflow automation.
Enable DS & Risk teams to build, test, and deploy models with minimal engineering bottlenecks.
Expand decisioning systems across functional pods—credit, pricing, collections, fraud, cross-sell, customer management—to drive consistent, explainable, and auditable decision-making.
Ensure the platform is scalable, modular, and compliant with RBI regulations.
Build modern, scalable data platforms (real-time ingestion, lakehouse, event-driven systems).
Ensure full lifecycle governance of data from sourcing to archival.
Partner with governance teams to enable lineage, auditability, and regulatory compliance.
Lead DataOps, L1/L2 support, and SRE teams to maintain >99.5% platform uptime.
Implement automated testing, proactive monitoring, and self-healing systems.
Optimize infra utilization and cloud cost efficiency.
• Business Delivery & Stakeholder Engagement
Act as execution partner to the Head of Product & Strategy and functional leaders.
Deliver platform capabilities and decisioning products aligned to business KPIs (loan volume growth, risk reduction, ticket size expansion, collections efficiency).
Manage technology partnerships and vendor ecosystems (e.g., Databricks, automation tools).
15 ~ 20 years of experience in data engineering, ML engineering, or platform leadership, with at least 8 ~10 years in senior management roles.
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Proven success in building and scaling large-scale data/ML platforms in fast-paced environments (fintech preferred).
Strong academic foundation with Bachelor’s/Master’s/PhD in Computer Science, Engineering, or quantitative fields from top-tier Indian institutions (IIT/IISc/BITS/NIT).
Deep expertise in data platform design (streaming, lakehouse, event-driven, real-time ingestion).