The Head of Data is responsible for leading and scaling the company's end-to-end data ecosystem, including data strategy, data engineering, business intelligence, analytics, and data governance.
This role plays a critical part in enabling data-driven decision-making across both productive lending (SME/business loans) and consumer lending, ensuring scalability, reliability, and regulatory compliance.
Data Strategy & Leadership
- Define and execute the company's data strategy and roadmap aligned with business objectives
- Build, lead, and develop a high-performing data team, including Data Engineers, BI Analysts, Data Analysts, and Data Scientists
- Act as a strategic partner to senior leadership in driving data-driven decisions
Data Engineering & Architecture
- Own and manage the company's data infrastructure, including data warehouse, data lake, and pipelines
- Ensure data systems are scalable, reliable, and secure
- Oversee integration of data from multiple sources: Core lending systems; Payment and transaction systems; Third-party providers (credit bureaus, e-KYC, etc.)
- Enable real-time or near real-time data availability where required
Business Intelligence & Analytics
- Oversee the development of dashboards and reporting frameworks across the organization
- Deliver insights on: Portfolio performance (disbursement, PAR, NPL), Customer acquisition, conversion, and retention, Customer segmentation and behavior
- Establish a single source of truth and standardize business metrics
Data Advanced Analytics
- Lead development of advanced analytics and predictive models, including: Credit risk scoring models (consumer & SME) . Fraud detection models, Collections and recovery optimization models
- Drive experimentation (A/B testing, uplift modeling) to support product and growth initiatives
Data Governance & Compliance
- Establish and enforce data governance frameworks, policies, and standards
- Ensure compliance with regulatory requirements (e.g., financial services regulators)
- Implement: Data quality management, Data lineage and documentation, Data access control and security
6. Business Impact & Collaboration
- Translate complex data into actionable insights and business recommendations
- Partner closely with Risk, Product, Growth, Operations, and Collections teams
- Drive measurable impact on: Revenue growth , Risk optimization , Operational efficiency
Requirements
- 10+ years of experience in Data, Analytics, Data Engineering, or Data Science
- 5+ years in a leadership role managing data teams
- Experience in fintech, P2P lending, banking, or financial services
- Strong understanding of both: Consumer lending, SME / productive lending
- Experience building data functions from scratch
- Exposure to regulatory reporting and compliance in financial services
- Experience in high-growth or scaling organizations
Technical Skills
- Advanced SQL, Proficiency in Python (preferred)
- Experience with data warehouses: BigQuery, Snowflake, Redshift
- ETL/ELT tools: Airflow, dbt
- Data pipeline design and orchestration
- API integration and data ingestion
- BI tools: Tableau, Power BI, Looker
- Strong data visualization and storytelling skills
- Machine learning techniques (regression, classification, clustering)
- Credit risk modeling concepts: Probability of Default (PD) , Loss Given Default (LGD) , Exposure at Default (EAD)
- Cloud platforms: GCP, AWS, or Azure
- Familiarity with big data tools (e.g., Spark) is a plus
