Head of Data & ML Platform
Bengaluru, India
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingBuild and scale ML engineering and data engineering functions.
Design and operationalize a centralized decisioning platform that integrates low-code model development, AutoML, rule engines, and workflow automation.
Build modern, scalable data platforms (real-time ingestion, lakehouse, event-driven systems).
From the employer’s posting
Data & ML Engineering Leadership Build and scale ML engineering and data engineering functions. Establish MLOps frameworks for standardized, production-grade model development and monitoring.
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.
Core Platform & Lifecycle Management Build modern, scalable data platforms (real-time ingestion, lakehouse, event-driven systems). Ensure full lifecycle governance of data from sourcing to archival.
Tools in this posting
- Python
- SQL
- AWS
- Azure
- Databricks
- Hadoop
- Kubernetes
- MLflow
- Spark
- Java
- Scala
- Google Cloud (GCP)
- Kafka
- Docker
- SageMaker
- scikit-learn
- PyTorch
- TensorFlow
- Airflow
Source — Tool mentions in context
- Strong understanding of data governance, lineage, and compliance frameworks in regulated industries (RBI, GDPR). - Solid programming and scripting experience (Python, SQL, Scala/Java) with knowledge of ML/DL libraries (TensorFlow, PyTorch, Scikit-learn). - Track record of driving platform reliability, resilience, and performance through DataOps and SRE practices.
- Expertise in distributed computing and big data frameworks (Spark, Hadoop, Kafka, Flink). - Proficiency in cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker). - Strong understanding of data governance, lineage, and compliance frameworks in regulated industries (RBI, GDPR).
- 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). Required Skills & Qualifications
- Experience operationalizing decisioning platforms combining rules, ML, AutoML, and workflow automation. - Expertise in distributed computing and big data frameworks (Spark, Hadoop, Kafka, Flink). - Proficiency in cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker).
- Deep expertise in data platform design (streaming, lakehouse, event-driven, real-time ingestion). - Hands-on knowledge of MLOps frameworks (MLflow, Kubeflow, Airflow, SageMaker, Vertex AI). - Strong background in model lifecycle management—deployment, monitoring, retraining, and governance.
About Credit Saison India
Established in 2019, CS India is one of the country’s fastest growing Non-Bank Financial Company (NBFC) lenders, with verticals in wholesale, direct lending and tech-enabled partnerships with Non-Bank Financial Companies (NBFCs) and fintechs.
In the employer’s words · Read in context
Job description
- 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.
- 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).
- Hands-on knowledge of MLOps frameworks (MLflow, Kubeflow, Airflow, SageMaker, Vertex AI).
- Strong background in model lifecycle management—deployment, monitoring, retraining, and governance.
- Experience operationalizing decisioning platforms combining rules, ML, AutoML, and workflow automation.
- Expertise in distributed computing and big data frameworks (Spark, Hadoop, Kafka, Flink).
- Proficiency in cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker).
- Strong understanding of data governance, lineage, and compliance frameworks in regulated industries (RBI, GDPR).
- Solid programming and scripting experience (Python, SQL, Scala/Java) with knowledge of ML/DL libraries (TensorFlow, PyTorch, Scikit-learn).
- Track record of driving platform reliability, resilience, and performance through DataOps and SRE practices.
- Ability to manage and optimize infra utilization and cloud costs at scale.
- Excellent leadership skills with experience managing 15+ member teams across engineering and platform functions.
- Strong communication, stakeholder management, and vendor negotiation skills to bridge business and technology.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on creditsaisonin-talent.freshteam.com. The employer’s form will show what is required.
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Source & posting history
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Bengaluru, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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- Status in our records
- Active
- First seen by us
- Jun 3, 2026
- Recorded sightings
- 16
- Last seen by us
- Sep 29, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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