Product Manager – Data & ML Evaluation (Enterprise) [UAEN]
Summary
Product Manager owning the end-to-end product data ecosystem, ML evaluation frameworks, and A/B testing strategies for AI-driven enterprise products, working cross-functionally with Engineering and Data Science teams.
Our client is seeking a highly analytical and
technically strong Product Manager – Data & ML Evaluation to lead
the strategy and execution of product data, experimentation, and machine
learning evaluation.
In this role, you will act as the product owner for
data and evaluation frameworks, ensuring that AI-driven products are
measurable, reliable, and continuously improving. You will work
cross-functionally with Product, Engineering, Data Science, and business
stakeholders to deliver high-impact, data-driven solutions.
Key Responsibilities:
· Product Data & Analytics
Ø Own and manage the end-to-end product
data ecosystem, including telemetry, tracking plans, event schemas, data
quality, and warehousing
Ø Define and implement a product metrics
framework (north star metrics, leading indicators, input metrics)
Ø Enable stakeholders with accessible
dashboards and actionable insights across products and platforms
· ML Evaluation & Experimentation
Ø Design and own machine learning
evaluation frameworks, including test set curation and KPI definition
(quality, safety, bias, latency, cost)
Ø Run and optimize offline and online
evaluations for AI models and features
Ø Build scalable and reproducible evaluation
pipelines integrated with CI/CD workflows
Ø Lead A/B testing and experimentation
strategies, including designing, analyzing, and scaling testing frameworks
· Strategy & Governance
Ø Drive data-informed pricing strategies by analyzing usage patterns, feature value, and cost structures
Ø Establish and enforce data governance
standards, including event naming, privacy, PII handling, and data
retention policies
Ø Collaborate with Security, Legal, and
business teams to ensure compliance and best practices.
Requirements
· Proven experience owning product analytics, instrumentation, and experimentation frameworks
· Strong proficiency in SQL and data analysis, with the ability to validate and interpret experiments independently
· Hands-on experience working with machine learning products, including model evaluation and monitoring
· Strong understanding of A/B testing methodologies and statistical concepts (e.g., power, MDE, guardrail metrics)
· Excellent stakeholder management and communication skills across technical and business teams
· Ability to operate effectively in fast-paced, cross-functional environments.
Preferred Qualifications
· Exposure to LLM / RAG evaluation frameworks, safety metrics, and AI model testing methodologies
· Familiarity with data modeling tools (e.g., dbt), feature stores, and observability platforms
· Experience working in regulated or privacy-sensitive environments
· Comfort leveraging AI tools to prototype analyses, dashboards, or lightweight data utilities
Work Location
· Abu Dhabi
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