Lead AI UnitSenior Lead AI Unit

Pune - India

Monthly Salary: Not Disclosed

Posted on: 8 hours ago

Vacancies: 1 Vacancy

Job Summary

Job Purpose	We are looking for a leader who can build and run AI product Pods for Credit Risk Fraud Risk Management and collection & recovery. This role will power next-generation decisioning across lending lifecycle- understanding lifecycle- underwriting portfolio monitoring fraud controls early warning allocation strategy optimization and recovery uplift by delivering production-grade ML systems with measurable impact. This is highly cross-functional role requiring deep technical leadership strong execution discipline and hands-on experience operating large scale distributed machine learning frameworks. (Training fine-tuning serving) under BFSI governance security and model risk constraints.
Duties and Responsibilities	Own the AI Pod operating model across Credit Risk Fraud/FRM and collections/Recovery: outcomes roadmap delivery cadence and cross-team dependencies. Lead end-to-end model lifecycle: problem framing feature strategy training evaluation development monitoring and continuous improvement with clear scorecards per use-case. Build large-scale ML systems: distributed training pipelines feature stores model registry CI/CD for ML and scalable batch near-real-time scoring services. Deliver Credit & Risk models: application/behavior risk models limit assignment early warning signals portfolio monitoring and policy optimization. Deliver Frau & FRM systems: fraud propensity/risk scoring anomaly detection identity/device/channel signals using Graph Machine Learning. Deliver collection & recovery optimization: roll-rate/cure/flow models contactability propensity-to-pay and recovery forecasting. Define operating models: SLIs/SLOs incident response and stakeholder cadence. Hire develop and scale the team: drive standards for quality safety and reliability.
Required Qualifications and Experience	Basic Qualifications: Bachelors/Masters in CS/Math/Engineering (PhD preferred in Large scale Machine learning systems) 10 years experience in Data Science /Applied ML/ ML Engineering with proven leadership delivering production grade ML system at scale. Demonstrated success shipping models with measurable business impact in credit risk fraud/FRM and /or collection & recovery. Required Skills & Competencies Core (must-have) Large-scale model training & Fine-tuning: experience with distributed training efficient fine -tuning patterns model versioning reproducibility and cost/performance trade-offs. ML evaluation rigor: calibration stability/drift bias/fairness checks leakage prevention robust back-testing and champion-challenger frameworks. Production mindset: ability to translate business objectives into ML systems with strong monitoring alerting and operational playbooks. Engineering & Tooling Strong coding ability in Python (and Java/Scala as needed); ability to prototype rapidly and productize. Distributed systems knowledge: scaling caching sharding HA performance tuning for both training and serving. Experience with common stacks: feature stores model registry experiment tracking vector/graph where relevant stream/batch processing Kubernetes CI/CD. Observability: logging/metrics/tracing incident management SLO-driven operations. Experience with data and compute stacks: Spark Kafka/streaming Lakehouse/warehouse APIs/microservices. Governance Security and Compliance Designing for BFSI constraints: PII handling policy enforcement auditability access controls. Risk-aware engineering mindset: safe tool execution approval workflows and secure-by-design approval workflows and secure by design patterns. Leadership Behaviors High ownership structured thinking and ability to drive clarity in ambiguous environments.

Required Experience:

Senior IC

Job PurposeWe are looking for a leader who can build and run AI product Pods for Credit Risk Fraud Risk Management and collection & recovery. This role will power next-generation decisioning across lending lifecycle- understanding lifecycle- underwriting portfolio monitoring fraud controls early war...

Job Purpose	We are looking for a leader who can build and run AI product Pods for Credit Risk Fraud Risk Management and collection & recovery. This role will power next-generation decisioning across lending lifecycle- understanding lifecycle- underwriting portfolio monitoring fraud controls early warning allocation strategy optimization and recovery uplift by delivering production-grade ML systems with measurable impact. This is highly cross-functional role requiring deep technical leadership strong execution discipline and hands-on experience operating large scale distributed machine learning frameworks. (Training fine-tuning serving) under BFSI governance security and model risk constraints.
Duties and Responsibilities	Own the AI Pod operating model across Credit Risk Fraud/FRM and collections/Recovery: outcomes roadmap delivery cadence and cross-team dependencies. Lead end-to-end model lifecycle: problem framing feature strategy training evaluation development monitoring and continuous improvement with clear scorecards per use-case. Build large-scale ML systems: distributed training pipelines feature stores model registry CI/CD for ML and scalable batch near-real-time scoring services. Deliver Credit & Risk models: application/behavior risk models limit assignment early warning signals portfolio monitoring and policy optimization. Deliver Frau & FRM systems: fraud propensity/risk scoring anomaly detection identity/device/channel signals using Graph Machine Learning. Deliver collection & recovery optimization: roll-rate/cure/flow models contactability propensity-to-pay and recovery forecasting. Define operating models: SLIs/SLOs incident response and stakeholder cadence. Hire develop and scale the team: drive standards for quality safety and reliability.
Required Qualifications and Experience	Basic Qualifications: Bachelors/Masters in CS/Math/Engineering (PhD preferred in Large scale Machine learning systems) 10 years experience in Data Science /Applied ML/ ML Engineering with proven leadership delivering production grade ML system at scale. Demonstrated success shipping models with measurable business impact in credit risk fraud/FRM and /or collection & recovery. Required Skills & Competencies Core (must-have) Large-scale model training & Fine-tuning: experience with distributed training efficient fine -tuning patterns model versioning reproducibility and cost/performance trade-offs. ML evaluation rigor: calibration stability/drift bias/fairness checks leakage prevention robust back-testing and champion-challenger frameworks. Production mindset: ability to translate business objectives into ML systems with strong monitoring alerting and operational playbooks. Engineering & Tooling Strong coding ability in Python (and Java/Scala as needed); ability to prototype rapidly and productize. Distributed systems knowledge: scaling caching sharding HA performance tuning for both training and serving. Experience with common stacks: feature stores model registry experiment tracking vector/graph where relevant stream/batch processing Kubernetes CI/CD. Observability: logging/metrics/tracing incident management SLO-driven operations. Experience with data and compute stacks: Spark Kafka/streaming Lakehouse/warehouse APIs/microservices. Governance Security and Compliance Designing for BFSI constraints: PII handling policy enforcement auditability access controls. Risk-aware engineering mindset: safe tool execution approval workflows and secure-by-design approval workflows and secure by design patterns. Leadership Behaviors High ownership structured thinking and ability to drive clarity in ambiguous environments.

Required Experience:

Senior IC

Key Skills

Administrative Skills
Facilities Management
Biotechnology
Creative Production
Design And Estimation
Architecture

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Bajaj Finance Limited

Bajaj Finserv is India’s most diversified non-banking finance company. Visit the website to learn about our products. Get instant approval on loans, shop on EMIs, make an investment, get insurance and pay your bills.

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