AI Product Analyst

Company Overview

Role Overview

Responsibilities

• Define and execute the analytics strategy for AI-powered products, machine learning models, and intelligent automation initiatives.
• Establish scalable data frameworks, KPIs, and measurement systems to evaluate AI product performance and business impact.
• Partner with AI Engineers, Data Scientists, Product Managers, and Development teams to translate business requirements into analytical roadmaps.
• Develop methodologies to monitor model performance, prediction accuracy, user adoption, drift detection, and overall AI effectiveness.
• Design and evaluate experiments, A/B tests, and AI model comparisons to optimise product outcomes.
• Analyse customer behaviour, trading patterns, engagement funnels, and operational workflows to identify AI-driven improvement opportunities.
• Build executive dashboards and reporting frameworks that clearly communicate AI performance and commercial value to senior stakeholders.
• Ensure data quality, consistency, and governance across AI systems, analytics platforms, and customer-facing applications.
• Create and maintain documentation for AI metrics, model definitions, event taxonomies, and analytical processes.
• Lead, mentor, and develop a team of Product Analysts while fostering a data-driven culture across the organisation.

Requirements

• 5+ years of experience in Product Analytics, Data Analytics, AI Analytics, Data Science, or a related field.
• Strong hands-on expertise in SQL and analysing large-scale datasets, customer journeys, transactional data, and behavioural analytics.
• Experience supporting AI, Machine Learning, Generative AI, or intelligent automation products in production environments.
• Strong understanding of machine learning concepts, model evaluation metrics, feature engineering, and AI performance monitoring.
• Proven experience designing and analysing experiments, A/B testing frameworks, and statistical significance methodologies.
• Experience with analytics and observability platforms such as Mixpanel, Amplitude, GA4, Segment, Datadog, Grafana, or similar tools.
• Familiarity with cloud-based analytics environments and modern data platforms, including AWS, Azure, GCP, Snowflake, Databricks, or equivalent.
• Knowledge of financial markets, trading platforms, fintech products, CFDs, cryptocurrency, or digital asset ecosystems is highly desirable.
• Excellent stakeholder management, communication, and presentation skills, with the ability to influence senior leadership.
• Experience measuring and optimising Generative AI applications, LLM-based products, AI assistants, recommendation systems, or predictive analytics solutions is preferred.
• Familiarity with MLOps concepts, model lifecycle management, and AI governance frameworks is advantageous.
• Experience within regulated industries such as financial services, banking, fintech, or capital markets is preferred.
• Strong business acumen and the ability to connect AI initiatives to measurable commercial outcomes.