Data Scientist Pricing

About noon

We're building an ecosystem of digital products and services that power everyday life across the Middle East—fast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and we're looking for a Pricing Data Scientist who can help us move even faster.

Noon's fastest hyper-local delivery platform, Noon Minutes, offers a localized assortment of FMCG & grocery products with delivery within 15-minutes. Currently live across the UAE and Saudi Arabia, offering thousands of products to customers in record time.

noon's mission: Every door, every day.

What you'll do:

Team noon has some of the fastest, smartest, and hardest-working people we've encountered. With a young, aggressive, and talented team, we're driving major missions forward. Pricing is one of the most important levers in our business — balancing customer conversion, sales, margin, competitiveness and long-term price perception across thousands of SKUs and stores. As a Pricing Data Scientist, you will work closely with Product, Commercial, Engineering and Data Science teams to build data-driven pricing systems that determine what price we should charge, where, and when.

• Build and improve SKU-level price elasticity models to understand how changes in price impact demand, conversion and revenue.
• Develop models to identify competitor-sensitive SKUs and quantify the impact of competitive price differences.
• Build price-demand curves to estimate potential sales at different price points and identify optimal prices.
• Develop models to optimise pricing across key business objectives including conversion, GMV, PC1 and customer competitiveness.
• Incorporate promotions, discounts, campaigns and other demand drivers into pricing and demand models.
• Translate models into production pricing algorithms and decision systems.
• Design and analyse experiments to measure the impact of pricing changes and continuously improve the models.
• Develop methods to handle sparse data, promotions, seasonality, cannibalisation and other real-world pricing challenges.
• Build monitoring and diagnostics to identify when pricing models are performing poorly or when market conditions change.
• Work hands-on with large datasets using SQL and Python and independently investigate business problems.
• Communicate model outputs and recommendations clearly to commercial and business stakeholders.

What you'll need

• 1-3 years of experience in Data Science, Applied Science, ML or a related quantitative field.
• Strong understanding of statistics, machine learning and causal inference.
• Strong experience with Python and SQL.
• Good understanding of regression, experimentation, forecasting and optimisation.
• Experience building models that have been deployed and used in real business decisions.
• Strong analytical thinking and ability to translate ambiguous business problems into quantitative models.
• Comfortable working with large, messy datasets and independently finding insights.
• Strong communication skills — ability to explain complex modelling concepts to non-technical stakeholders.
• Experience in pricing, retail, e-commerce, quick-commerce, FMCG or marketplaces is a strong plus.

Who will excel

• We're looking for people with high standards, who understand that hard work matters.
• You need to be relentlessly resourceful and operate with a deep bias for action.
• We need people with the courage to be fiercely original.
• noon is not for everyone; readiness to adapt, pivot, and learn is essential.