Company Overview

Our client, a global regulated financial services group with a strong presence across international markets, provides online trading and investment solutions across FX, CFDs, commodities, indices, equities, and digital assets. With a growing focus on technology, data, and Artificial Intelligence, the organisation is investing in AI-powered products, intelligent automation, customer intelligence, and scalable digital platforms to enhance client experience and operational performance.

Role Overview

We are seeking an AI Product Analyst to drive the analytical foundation of the organisation's AI and data initiatives. This role sits at the intersection of Artificial Intelligence, Product Analytics, and Financial Technology, helping shape AI-powered products, automation solutions, customer intelligence platforms, and data-driven decision-making across the business.

The successful candidate will partner with Product, Engineering, Data Science, AI Engineering, and Business teams to measure product performance, identify opportunities for AI adoption, define success metrics, and generate actionable insights that accelerate innovation. You will also lead a team of Product Analysts while establishing best practices for AI product measurement, experimentation, and governance.

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.