Head of AI & BI Reporting
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Key skills for this role
About the Role
A global regulated financial services group seeks a Head of AI & BI Reporting to lead enterprise-wide AI, BI, data analytics, and reporting functions. The role involves building a data-driven culture, accelerating AI adoption, and delivering advanced analytics to support business growth and executive decision-making.
Key Skills for This Role
Responsibilities
- Define and execute the enterprise AI, Analytics, and Business Intelligence strategy in line with corporate objectives
- Lead the development and deployment of AI, Machine Learning, Generative AI, predictive analytics, and intelligent automation solutions across business functions
- Establish AI governance frameworks, model monitoring standards, explainability practices, and responsible AI policies
- Build end to end analytical frameworks covering the customer lifecycle
- Develop enterprise KPI frameworks and executive dashboards across trading, operations, marketing, finance, and customer experience
- Leverage predictive models such as churn prediction, propensity scoring, customer lifetime value modelling, and recommendation engines
- Design advanced customer segmentation models using clustering techniques and behavioural feature engineering
- Conduct funnel analysis using event level data, clickstream analytics, customer journeys, and platform interaction data
- Apply attribution methodologies to assess marketing effectiveness and ROI
- Oversee scalable analytics pipelines using SQL, Python, and cloud based data platforms
- Lead, mentor, and scale high performing teams across AI, Data Science, BI, Analytics, and Reporting
Requirements
- Bachelor’s or Master’s degree in Data Science, Artificial Intelligence, Computer Science, Statistics, Mathematics, Engineering, Business Analytics, or a related field
- 10+ years of experience in AI, data science, BI, or analytics leadership roles
- Proven experience leading AI and analytics teams in financial services or regulated environments
- Strong expertise in AI/ML, predictive modeling, generative AI, and intelligent automation
- Experience with BI tools, data platforms, and cloud infrastructure
- Excellent leadership, communication, and stakeholder management skills
Full Job Posting
Role Overview
- The Head of AI & BI Reporting will lead the organisation’s enterprise wide Artificial Intelligence, Business Intelligence, Data Analytics, and Reporting functions.
- This strategic leadership role will be responsible for building a data driven culture, accelerating AI adoption, and delivering advanced analytics capabilities that support business growth, operational excellence, customer engagement, and executive decision making.
- The successful candidate will oversee AI initiatives, predictive analytics, BI reporting, customer intelligence, experimentation frameworks, and enterprise analytics platforms.
Responsibilities
- Define and execute the enterprise AI, Analytics, and Business Intelligence strategy in line with corporate objectives.
- Lead the development and deployment of AI, Machine Learning, Generative AI, predictive analytics, and intelligent automation solutions across business functions.
- Establish AI governance frameworks, model monitoring standards, explainability practices, and responsible AI policies.
- Identify opportunities where AI and advanced analytics can improve revenue growth, customer engagement, retention, operational efficiency, and risk management.
- Evaluate emerging AI technologies, platforms, and tools to maintain a competitive advantage within financial services.
- Build end to end analytical frameworks covering the customer lifecycle, including acquisition, activation, retention, monetisation, and lifetime value.
- Develop enterprise KPI frameworks and executive dashboards across trading, operations, marketing, finance, and customer experience.
- Leverage predictive models such as churn prediction, propensity scoring, customer lifetime value modelling, and recommendation engines to support decision making.
- Design advanced customer segmentation models using clustering techniques and behavioural feature engineering.
- Conduct funnel analysis using event level data, clickstream analytics, customer journeys, and platform interaction data.
- Apply attribution methodologies, including rule based attribution, probabilistic attribution, and Marketing Mix Modelling, to assess marketing effectiveness and ROI.
- Translate complex data, predictive model outputs, and AI generated insights into commercially actionable recommendations for senior stakeholders.
Experimentation & Optimisation
- Design and evaluate experimentation frameworks, including A/B testing, multivariate testing, uplift modelling, and causal measurement.
- Establish governance and best practices for hypothesis testing, experimentation design, and performance measurement.
- Monitor and optimise customer acquisition cost, activation, retention, engagement, churn, conversion, and lifetime value metrics.
Data Engineering & Reporting
- Oversee scalable analytics pipelines using SQL, Python, and cloud based data platforms.
- Build automated reporting, forecasting, monitoring, and anomaly detection solutions using AI powered analytics tools.
- Ensure data quality, consistency, governance, security, and regulatory compliance across reporting and analytics environments.
- Manage structured, semi structured, and event driven datasets from trading platforms, CRM systems, marketing technologies, web applications, and third party sources.
- Drive self service analytics adoption through modern BI tools and data democratisation initiatives.
Leadership & Stakeholder Management
- Lead, mentor, and scale high performing teams across AI, Data Science, BI, Analytics, and Reporting.
- Partner with Product, Marketing, Technology, Trading, Finance, Risk, Compliance, and Operations teams to align analytics initiatives with business priorities.
- Present AI roadmaps, strategic insights, and performance updates to executive leadership.
- Foster a culture of experimentation, innovation, accountability, and data driven decision making.
Requirements
- Bachelor’s or Master’s degree in Data Science, Artificial Intelligence, Computer Science, Statistics, Mathematics, Engineering, Business Analytics, or a related field.
- 10+ years of experience in AI, data science, BI, or analytics leadership roles.
- Proven experience leading AI and analytics teams in financial services or regulated environments.
- Strong expertise in AI/ML, predictive modeling, generative AI, and intelligent automation.
- Experience with BI tools, data platforms, and cloud infrastructure.
- Excellent leadership, communication, and stakeholder management skills.
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