Head of Data & Credit Analytics - TradePay

Sanabil Studio is a venture builder that blends industry expertise, technology, and startup know-how to turn bold ideas into real businesses. We take concepts from zero to launch, and when a venture proves its potential, we back it with seed funding and hands-on support to help it scale. TradePay is one of those ventures building the trade finance infrastructure for FMCG in Saudi Arabia. Our mission is to replace informal supplier credit with structured, data-driven working capital that helps small merchants grow, protects suppliers from credit risk, and strengthens the FMCG supply chain. We are building a new credit system for underbanked merchants where risk is priced from real transaction behavior, not balance sheets. Our model leverages supplier, distributor, and marketplace data to power embedded B2B BNPL experiences across FMCG ecosystems. This is not traditional lending — this is supply-chain-native decisioning built from real commerce data. We are looking for a Head of Data & Credit Analytics to build and lead TradePay's decision science, fraud, and portfolio analytics function from the ground up — reporting directly to the Founder. THE ROLE What you'll own here. -Build and own TradePay's merchant scoring and decisioning frameworks -Develop underwriting, fraud detection, and portfolio monitoring models using supplier, marketplace, and behavioral data -Design and optimize credit limit allocation, utilization logic, pricing models, and repayment segmentation -Build analytical frameworks around SKU velocity, merchant behavior, repayment patterns, and transaction frequency -Partner with Product and Engineering to embed real-time decisioning into operational systems and APIs -Develop fraud detection logic and merchant anomaly monitoring systems -Build dashboards, portfolio reporting, and early warning indicators for operational and executive teams -Design experiments and analytical tests to optimize approval rates, utilization, repayment behavior, and portfolio health -Define and manage data pipelines, data quality standards, and analytical governance -Support future AI/ML evolution of TradePay's underwriting and risk engine -Hire and lead future data science and analytics team members How Success Will Be Measured Model accuracy and approval rates, portfolio performance and repayment quality, fraud detection effectiveness, speed and reliability of real-time decisioning, and the strength of the analytical foundations as TradePay scales. Where This Role Can Go Head of Data & Credit Analytics → Chief Data Officer as TradePay scales its underwriting and risk engine across the region. THE PROFILE You're probably a fit if… You have 6+ years of experience in data science, credit analytics, decisioning, or fintech analytics, with 2+ years in a leadership or senior individual contributor role You're hands-on technical with strong SQL and Python skills You've built underwriting, fraud, or risk models in fintech, BNPL, SME lending, merchant acquiring, or payments You've worked with alternative or behavioral data models You have a strong grasp of portfolio analytics, repayment behavior, utilization analysis, and risk segmentation You've built dashboards and analytical reporting frameworks from scratch You can work in ambiguity and build systems from zero in an early-stage environment You communicate clearly and can translate complex analytical concepts into business insights You have a builder mentality with strong ownership and execution bias You're fluent in Arabic and English Bonus: experience in B2B BNPL, merchant finance, supply chain finance, SME lending, FMCG, marketplaces, embedded finance, fraud analytics, real-time decisioning systems, ML pipelines, or MENA and emerging markets THE ENVIRONMENT What working here actually looks like. 1- Core Engine Ownership You own the underwriting and analytics engine that powers the entire business. Every credit decision, every fraud check, every portfolio insight runs through what you build. 2- Direct Impact on the Business Portfolio performance, profitability, and product strategy all trace back to your models. What you build moves the numbers directly. 3- A Role That Grows With You This position has a clear path into Chief Data Officer as TradePay scales its underwriting and risk engine across the region. What You Get From Us Competitive pay: A package that reflects your experience and the market, not a lowball with "equity upside" as the excuse. Meaningful equity: Real upside aligned with long-term value creation. Real data, at scale: Access to real-world FMCG transaction data across suppliers, distributors, and marketplaces the foundation of a category-defining fintech. Premium gear, day one: Everything you need to hit the ground running, set up and ready before your first morning. Mentorship that matters: Direct collaboration with the Founder and leadership team from people who've actually built and scaled ventures. An accelerated curve: You'll learn more here in 12

6+ years in data science, credit analytics, decisioning, or fintech analytics; 2+ years in a leadership or senior individual contributor role; hands-on technical with strong SQL and Python skills; built underwriting, fraud, or risk models in fintech, BNPL, SME lending, merchant acquiring, or payments; worked with alternative or behavioral data models; strong grasp of portfolio analytics, repayment behavior, utilization analysis, and risk segmentation; built dashboards and analytical reporting frameworks from scratch; ability to work in ambiguity and build systems from zero in an early-stage environment; clear communication and ability to translate complex analytics into business insights; fluent in Arabic and English.

Build and own TradePay's merchant scoring and decisioning frameworks; develop underwriting, fraud detection, and portfolio monitoring models using supplier, marketplace, and behavioral data; design and optimize credit limit allocation, utilization logic, pricing models, and repayment segmentation; build analytical frameworks around SKU velocity, merchant behavior, repayment patterns, and transaction frequency; partner with Product and Engineering to embed real-time decisioning into operational systems and APIs; develop fraud detection logic and merchant anomaly monitoring systems; build dashboards, portfolio reporting, and early warning indicators for operational and executive teams; design experiments and analytical tests to optimize approval rates, utilization, repayment behavior, and portfolio health; define and manage data pipelines, data quality standards, and analytical governance; support future AI/ML evolution of underwriting and risk engine; hire and lead future data science and analytics team members.