Senior Manager Data Science

About Us Core42, a leader in AI-powered cloud and digital infrastructure, is driving transformative technology solutions globally. Leveraging advanced resources and partnerships, Core42 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.The OpportunityAs a Data Scientist at Core42, 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.ResponsibilitiesAnalyze 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.What We’re Looking For(a) Required Skills / QualificationsBackground 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., ClickHouse, BigQuery, 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, classifiers, scoring or ranking systems, or automated decisioning.Proven ability to partner with product and engineering to convert insights into customer-facing features.Fluency with AI and LLMs—how they behave and how they are evaluated—with informed views on model evaluation and the agentic ecosystem.Excellent written and verbal communication, with the ability to distill complex analysis into clear recommendations.(b) Preferred Skills / QualificationsExperience with LLM evaluation and benchmarking (online/offline evals, human-in-the-loop assessment, quality or safety guardrails).Familiarity with AI inference and model-serving concepts—latency, throughput, cost and routing—and how they shape customer experience.Experience with developer platforms, APIs/SDKs or usage-based products.Experience with data modeling and modern warehouse tooling (e.g., dbt, ClickHouse).NLP or machine learning engineering experience building classifiers, embeddings or ranking models.Experience in regulated, sovereign or enterprise environments.Familiarity with Microsoft Azure and Azure AI services, AWS or Google Cloud.Passion for innovation, curiosity and a bias for action aligned with Core42’s mission to conquer new frontiers in AI.How You WorkBias to action: you identify the highest-impact problem and go solve it rather than waiting for tickets.AI-first: you use modern AI tooling—coding agents, MCP servers and LLM workflows—heavily in your own work.Comfortable with ambiguity: you break down complex systems and data and find pragmatic paths forward.Strong written communication: you distill complex trade-offs into clear recommendations for technical and non-technical audiences.What Success Looks LikeInsights and data products measurably improve customer experience, adoption and retention.Experiments and analyses directly inform product, routing and roadmap decisions.Product metrics are well-defined, trusted and tied to decisions across the team.Customers can understand and optimize their own AI usage through the features you ship.Analytical foundations scale with the business and raise the quality of decision-making.Role Scope and BoundariesThis is a hands-on, individual-contributor data science role focused on analysis, experimentation and data products that influence the product. It works alongside product managers, who own roadmap prioritization, and engineering teams, who own platform and production systems.The role informs product and roadmap decisions with data and evidence but does not own product strategy. Legal, risk, compliance and security stakeholders retain accountability for policy interpretation, approvals and control ownership.What working at Core42 offers With a diverse team of 1,100+ employees from 68 nationalities, we foster an inclusive, innovative and collaborative environment. At Core42, we foster a culture grounded in trust, accountability and high performance. We are united by our values: Grit, where we overcome challenges with resilience and determination, Passion, which drives us to pursue excellence in everything we do, and Impact, as we aim to inspire progress and create meaningful change. Our team members thrive in an environment where each person’s contributions propel us forward, and together, we commit to achieving extraordinary results.Competitive Salary: We offer an attractive salary package based on your skills and experienceYearly Bonus: In recognition of your contributions, you will receive a performance-based annual bonusExclusive Discount Cards: Access special benefits with Esaad and Fazaa cards, offering discounts across a wide range of servicesPremium Family Insurance: We provide comprehensive health coverage, including dental, vision and life insurance, ensuring the well-being of you and your familyLearning & Development: We offer access to top-tier learning platforms to help you grow in your career. Learn at your own pace with unlimited access to premium courses.