Head of Data Analytics & Science

As Head of Data, you will transform a 5-person team into a strategic growth engine , deploying AI across operations, CX, and risk, while pioneering innovation with voice, video, and alternative data .

Driving financial inclusion providing access to capital to underbanked unbanked MSMEs is one of our key goals. This role will drive building in-house underwriting models for MSMEs across sectors sizes, relying on both our existing ecosystem and external alternative data to help us achieve that goal.

Strategic Leadership

• Define and execute a data strategy tightly aligned with GTM, personalization, underwriting, and revenue growth

• Embed data into decision-making across product, engineering, risk, finance, and GTM teams

Credit, Risk Fraud

• Build advanced credit underwriting models leveraging payments, ecosystem, and alternative data

• Design a fraud and risk engine for near-real-time detection and intervention

• Experiment with unstructured data (voice, video, image) for product and risk innovation

AI Advanced Analytics

• Drive AI adoption across functions (ops, CX, risk, product)

• Lead innovation with voice, video, and alternative data signals to enhance personalization, underwriting, fraud detection, and customer engagement

• Scale predictive and prescriptive ML models to drive efficiency and growth

• Build a culture of experimentation (A/B testing, synthetic controls)

Data Infrastructure Governance

• Architect modern pipelines (streaming + batch) for low-latency decisioning

• Build frameworks for compliance, governance, and data privacy in fintech

• Ensure accuracy, reliability, and accessibility of data assets

Team Organization Building

• Scale the team into a high-performing organization and strategic partner

• Hire and mentor world-class data, ML, and risk talent

• Instill a culture of storytelling with data that drives executive and GTM action.

• 8 to 12 years in data leadership, ideally in fintech (payments, lending, fraud/risk).

• Hands-on expertise in payment flows, credit underwriting, fraud vectors, and AI/ML

• Proficiency in Python, SQL, ML frameworks, streaming architectures (Kafka/Flink/Spark), and visualization tools.

• Proven ability to link analytics to business growth and financial impact

• Strong stakeholder management and communication skills

• Familiarity with compliance, governance, and cross-border fintech data requirements.

1. Build and launch next-gen credit underwriting models .

2. Deliver a fraud risk engine that improves trust and reduces losses

3. Scale AI-led initiatives , including voice/video innovations across ops, CX, and product

4. Grow the data org into a strategic revenue enabler