Senior Manager - Data Science

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, who can help us move even faster.

noon’s mission: Every door, every day.

What you'll do

• Applied AI, analytics automation and internal tools (must have)• Lead analytics automation by connecting LLMs to governed data: certified metrics, curated tables and semantic layers.
• Ensure AI-generated insights are accurate, explainable and secure, with clear evaluation, transparency and data governance built in from the start.
• Build internal tools and self-serve products that help teams answer their own questions and reduce ad-hoc requests.
• Spot opportunities nobody has asked for yet, and turn the best into solutions teams actually adopt.
• Data science• Build solutions that shape how customers discover, engage with, and buy on noon, from personalized recommendations to a smarter, more relevant app experience.
• Choose the simplest method that works, and measure models on business outcomes, not just offline accuracy.
• Product analytics and experimentation• Partner with PMs on what to build and how to measure it: North Star and guardrail metrics, funnels, cohorts, opportunity sizing and A/B test design and readouts.
• Own experimentation standards, from randomization, power and pre-registered metrics to novelty effects and clear ship/kill decisions.
• Push back when the data doesn't support a decision, and propose what to do instead.
• Lead and grow the team• Manage analysts and data scientists: hiring, goals, reviews, coaching and hard performance conversations when needed.
• Allocate capacity across squads and run a clear intake and prioritization process with Product.
• Raise the quality bar by reviewing analyses, test designs and models before they reach stakeholders.
• Communicate and influence• Turn complex data into clear recommendations and actionable stories for leadership.
• Build trust with Product, Engineering and Business by being direct, timely and right.

What you bring

• 7–9 years in product analytics, data science or growth analytics, ideally in e-commerce, marketplaces or consumer tech at scale.
• 2+ years managing analysts or data scientists as direct reports, including hiring, reviews and handling underperformance. Mentoring alone doesn't count.
• Strong SQL and Python, plus a cloud warehouse (Big Query preferred) and a BI tool (Looker preferred).
• Deep experimentation skills, including knowing when results can't be trusted.
• Production experience applying LLMs to analytics or internal tools, and the safeguards you added when things went wrong.
• Product thinking and clear communication with senior stakeholders, even when the answer isn't what they wanted.
• Nice to have• Text-to-SQL, RAG or agent workflows over a semantic layer or metric catalogue.
• Building internal data tools or self-serve analytics products.
• Recommendation systems, personalization or search ranking.
• Causal inference (difference-in-differences, synthetic control, uplift modelling).
• GCC or Arabic-language product experience.