Tamara
Fintech
SeniorDataScientist
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“Senior Data Scientist at Tamara”
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Full Job Description
About Us Tamara is the leading fintech platform in Saudi Arabia and the wider GCC region with a mission to help people make their dreams come true by building the most customer-centric financial super-app on earth. The company serves millions of users in the region and partners with leading global and regional brands such as SHEIN, Jarir, noon, IKEA and Amazon, as well as small and medium businesses. Tamara is Saudi Arabia’s first fintech unicorn and is backed by Sanabil Investments, a wholly owned company by the Public Investment Fund (PIF), SNB Capital, Checkout.com, amongst others. The company operates from its headquarters in Riyadh, with additional regional and global support offices. We are seeking a highly analytical and technically proficient Credit Risk Data Analyst to support our Portfolio Oversight team. In this role, you will be responsible for managing the health and performance of the credit portfolio. You will not only build the "Single Source of Truth" for risk data but also translate complex datasets into actionable strategies for underwriting, limit management, and loss forecasting. Key Responsibilities Develop Portfolio Monitoring reports for internal and external communications Design and optimize data-driven credit strategies, including underwriting criteria, credit limit assignments, risk-based pricing & merchant risk strategy Conduct deep-dive analysis on risk exposure versus profitability to identify opportunities for product expansion or de-risking. Develop and track Early Warning Indicators to detect abnormal risk trends and shifts in macroeconomic conditions Conduct rigorous A/B testing to verify hypotheses and evaluate the impact of strategy changes on portfolio profitability and delinquency Assess business operations & market trends to enhance competitive positioning Build and optimize automated data pipelines to enhance the efficiency and scalability of risk monitoring Perform continuous system analysis to identify data inconsistencies
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