Hiring: Lead Data Scientist / AI/ML Engineer

Location: Pune

Experience: 10-12 years

Mandatory (Education): B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are considered.

Mandatory (Age): Candidate's age should be below 37 years.

Key Skills:

- Machine Learning
- Python
- Spark
- Kafka
- Kubernetes
- Credit Risk Analytics
- Fraud Analytics
- Collections Analytics
- CI/CD

Roles:

- Lead AI Product Pods across Credit Risk, Fraud, and Collections functions.
- Build and deploy production-scale Machine Learning systems for lending lifecycle decisioning.
- Own complete ML lifecycle including feature engineering, model training, evaluation, deployment, monitoring, and continuous improvement.
- Design scalable distributed ML infrastructure, feature stores, model registries, and MLOps pipelines.
- Develop AI solutions for underwriting, portfolio risk monitoring, fraud detection, anomaly detection, and recovery optimization.
- Drive model governance, monitoring, explainability, and compliance within BFSI regulatory standards.
- Collaborate with Product, Risk, Engineering, Data, and Business teams to deliver AI-driven business outcomes.
- Define AI platform architecture, operational excellence, SLAs, and incident management practices.
- Build, mentor, and scale high-performing AI Engineering and Data Science teams.

Responsibilities:

- Strong Lead Data Science, AI Engineer, or Machine Learning Engineer profiles.
- Mandatory (Experience 1): Must have 10 years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.
- Mandatory (Experience 2): Must have hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery,



with proven delivery of business-impacting AI/ML solutions.
- Mandatory (Experience 3): Candidate's current designation must be Lead or above.
- Mandatory (Experience 4): Must have solid experience designing and deploying large-scale distributed Machine Learning systems, including model training, fine-tuning, inference, scalable serving, and production deployment.
- Mandatory (Experience 5): Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing.
- Mandatory (Experience 6): Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.
- Mandatory (Experience 7): Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, driving cross-functional execution, and managing production AI platforms.
- Mandatory (Experience 8): Must have experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, approval workflows, and model risk management practices.

Preferred (Experience 1): Candidates currently working as Lead / Principal / Engineering Manager / Associate Director / Director in reputed Product, FinTech, Banking, NBFC, or Global Capability Centers will be preferred.

Preferred (Experience 2): Indian professionals currently working overseas (NRI) who are planning to relocate and permanently settle in India are encouraged to apply.

Preferred (Experience 3): Experience building enterprise AI platforms using Graph ML, Vector Databases, LLM-enabled decisioning, distributed training frameworks, and large-scale AI infrastructure.

📌 Lead Data Scientist - Credit Risk & Fraud Analytics (India)
🏢 Freelance HR
📍 India