Analytics and Decision Support Manager

About the role

The Analytics and Decision Support Manager is the senior hands-on leader for enterprise analytics, data science, reporting and business decision support at World Business Lenders, reporting to the Chief Data and Analytics Officer within the IDEA department. The role leads two Team Leads and four Analysts, sets the analytical agenda, ensures metrics and methods are trustworthy, and turns ambiguous business questions into evidence, recommendations and reusable decision tools.

Key responsibilities

• Manage, coach and develop two Team Leads and four Analysts, set quality standards, feedback and accountability, and own the analytical agenda and resource plan.
• Prioritise demand by business impact, urgency, data readiness and capacity, and communicate clearly with stakeholders.
• Turn business questions into statistical analyses, predictive models, experiments, dashboards, forecasts, scenario models and recommendations, explaining assumptions, limitations and changes in results.
• Supply model evaluation and reproducible performance evidence for intelligence products, and advise senior leaders on findings, uncertainty and trade-offs.
• Establish consistent metric definitions, technical evaluation and documentation, and partner with data engineering and business teams to improve data quality, automate recurring work and expand self-service.
• Review recurring quality issues, agree improvements with business owners and track adoption.

Required profile

• At least 12 years of progressive experience in data science, analytics, business intelligence or quantitative decision support, including at least 5 years of people leadership and leading Team Leads or senior analytical staff.
• Demonstrated success building, scaling or improving an analytics function that delivers capabilities used in business decisions or production products.
• Recent hands-on analytical delivery is required; this is not a management-only role.
• Experience owning an analytics portfolio combining data science, executive reporting, KPIs, self-service analytics, forecasting, scenario modelling and ad hoc support.
• Experience developing predictive models with train/test design, backtesting, performance metrics, drift analysis and documentation of limitations.
• Experience defining enterprise metrics and building analytical tools and decision frameworks for operating, credit, pricing, portfolio, capital or strategic decisions.
• Experience supporting senior leaders in a fast-moving business, triaging demand by decision value, urgency and data readiness.
• Lending, credit, portfolio or financial-services analytics experience is helpful but not required.

Required skills

• SQL and Python or equivalent analytical tools, plus BI and visualization platforms.
• Deep working knowledge of statistical analysis, predictive modelling, model evaluation and backtesting, experimentation, forecasting, scenario analysis, feature development and reproducible workflows.