About us

Tamara is MENA’s leading payments innovator, focused on providing a seamless experience for merchants and customers through fair and transparent financial solutions. The company’s flagship Buy Now Pay Later platform lets shoppers split their payments online and in-store with no interest and no hidden fees. Tamara was founded in Riyadh, Saudi Arabia in late 2020 and has since grown to more than 250 employees in offices around the world in KSA, UAE, Germany, and Vietnam. The company’s $110 million Series A round in 2021 - led by Checkout.com - broke records as the largest ever in the Middle East and to date, it has raised $216 million in equity and debt. Tamara has over 4 million customers and more than 6,000 partner merchants, including leading global and regional brands like IKEA, SHEIN, Adidas, Namshi, and Jarir plus local SMEs. 

We’re looking for a Senior Data Scientist to join our Risk team to support our risk management operations.

What we are looking for 

  • Attitude: perseverance, curiosity, team-player, passion with data and science, critical thinking.
  • Theoretical experience: solid understanding on basic probability, statistics, data modeling (linear regression, decision tree, and logistic regression).
  • Data-driven and hands-on experience: ability to communicate, to explain and to model patterns in data, ability to translate loosely ideas into quantifiable statements.
  • Experience translating data into actionable insights business decisions
  • Experience with risk rating projects is a plus
  • 5+ years of experience in data / customer analytics and quantitative environments (for example: banking, trading, PhD program)

What you will do

  • Be active in developing risk initiatives and working on the analytical roadmap.
  • Discover actionable insights and provide recommendations to improve credit and fraud risk.
  • Work closely with product managers, data engineers, and risk managers to implement models in production.
  • Ensure a sound technical approach to credit and fraud modelling.
  • Conduct data analyses, modelling, and experiments that help us to understand the payment behaviors of customers from different aspects.
  • Coach and mentor junior members and create broader data awareness at organizational level.

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