Senior Manager Data Science

Core
42, a leader in AI-powered cloud and digital infrastructure, is driving transformative technology solutions globally. Leveraging advanced resources and partnerships, Core
42 empowers clients to harness sovereign AI infrastructure, especially in sectors with stringent regulatory needs. With a mission to redefine digital transformation, we combine sovereign capabilities with scalable, high-performance compute infrastructure, positioning itself at the forefront of AI innovation in the Middle East and beyond.

As a Data Scientist at Core
42, you will turn data from one of the region's largest AI inference platforms into better products and better decisions. Working across Compass, sovereign AI and enterprise LLM services, you will analyze how customers use AI, where they hit friction and what drives adoption, and translate those insights into product features, routing and optimization decisions, and roadmap direction.

Compass serves AI inference at national scale across sovereign cloud and HPC environments, spanning multiple models, providers and modalities and billions of generations. You will turn that production data into a clearer, faster and more cost-effective experience for every customer we support.

This is not a reporting role. You will own questions end to end—framing the problem, digging into the data and shipping the answer—whether that is a new analytics product for customers, a change to how we route or recommend models, or an insight that reshapes the roadmap. Your work shows up directly in the experience of every customer we serve.

• Analyze large-scale usage, performance and cost data to understand how customers use AI inference, where they hit friction and what drives adoption, retention and growth.
• Design and run experiments—A/B tests, causal analyses and statistical evaluations—to measure impact and guide product and routing decisions.
• Build and ship data products and user-facing features such as usage analytics, model-performance rankings, task classification and recommendations that help customers understand and optimize their AI usage.
• Develop models, classifiers and scoring or ranking systems that improve how models and providers are selected, recommended and surfaced to customers.
• Define and track product metrics—adoption, engagement, quality and platform health—and tie them directly to roadmap and architectural decisions.
• Partner closely with product, engineering and customer-facing teams to turn analysis into shipped features rather than one‑off reports.
• Contribute to the analytical data foundation—data models, pipelines and warehouse—so insights scale with the business.
• Evaluate model quality and behavior using online and offline evaluations, benchmarking and human‑in‑the‑loop assessment.
• Communicate findings and recommendations clearly to technical and non‑technical stakeholders, including senior leadership.

• Background in Computer Science, Data Science, Statistics, Mathematics or a related quantitative field;
  Master’s or PhD is a plus.
• 8+ years of experience in data science, applied ML or a quantitative product role, ideally at a high‑growth or high‑velocity company.
• Strong statistical and experimental foundations—experimental design, A/B testing and causal inference—thinking in distributions, not just averages and dashboards.
• Strong SQL skills, with the ability to write complex, performant queries against large‑scale analytical databases (e.g., Click House, Big Query, Snowflake or similar).
• Proficiency in Python (or a similar language) for analysis, prototyping models, running simulations and building data pipelines.
• Experience building and shipping production data products—models,…