Manager Business Performance at HF Group

• Design, develop, and maintain dashboards, scorecards, and performance reports for business units across the group.
• Automate recurring reports to improve efficiency and reduce manual processing effort.
• Present complex analytical findings in clear, accessible formats for both technical and non-technical stakeholders.

• Track and analyse performance across frontline functions, and back-office functions.
• Monitor branch performance, digital channel efficiency, and product profitability to surface opportunities and risks.
• Support the Head of Data and Analytics in maintaining enterprise-wide balanced scorecards.
• Contribute to workforce optimisation and cost efficiency analysis to inform strategic planning.

• Build and validate predictive models to forecast customer behaviour, credit risk, and product demand.
• Apply machine learning and statistical techniques to improve loan underwriting, fraud detection, and customer churn prediction.
• Conduct profitability and segmentation analyses to identify high-margin products, services, and customer groups.
• Support the ongoing development and refinement of AI/ML models for credit scoring and anti-money laundering (AML).

• Analyse customer transaction data, spending patterns, and lifestyle trends to generate actionable insights.
• Identify high-value customer segments to support targeted marketing campaigns and product strategies.
• Partner with business and product teams to enhance cross-selling and upselling strategies through data-driven recommendations.

• Ensure all data used for analytics and reporting meets governance, accuracy, and completeness standards.
• Implement and uphold data quality controls, escalating issues to the Head of Data and Analytics for resolution.
• Adhere to applicable regulatory and compliance standards (e.g., GDPR, CCPA, local banking regulations) in all analytics activities.

• Work closely with business units frontline functions and enabling functions to identify data needs and deliver tailored analytical solutions.
• Present insights and recommendations to senior management in a structured, decision-ready format.
• Engage with external vendors and data partners as directed by the Head of Data and Analytics.

• Supervise and mentor analysts within the team, fostering a culture of accountability, learning, and high performance.
• Assign, review, and quality-check analytical outputs to ensure accuracy and alignment with business priorities.
• Support onboarding and skills development of junior team members.

• Accurate, timely dashboards and performance reports delivered to business stakeholders on schedule.
• Validated predictive models supporting lending decisions, fraud detection, customer retention, and risk management.
• Customer segmentation and behavioural analyses informing marketing and product strategy.
• Standardised KPIs and metrics enabling consistent performance tracking across the Group.
• Data quality and governance compliance records maintained to required standards.

• Proficiency in BI and data visualisation tools such as Power BI or Tableau.
• Strong command of SQL for data extraction, manipulation, and analysis.
• Proficiency in Python and/or R for statistical analysis and machine learning.
• Experience with cloud-based data platforms (AWS, Azure, or Google Cloud).
• Familiarity with big data frameworks (Apache Spark, Kafka, or Hadoop) is an advantage.
• Ability to design self-service analytics solutions and interactive, executive-facing dashboards.
• Knowledge of KPI tracking methodologies, reporting automation, and visualisation best practices.

• Analytical Thinking: Ability to break down complex datasets and derive clear, actionable conclusions.
• Attention to Detail: High standards for data accuracy, consistency, and reporting integrity.
• Communication & Influence: Skilled at presenting complex findings to non-technical audiences in plain, persuasive language.
• Collaboration: Comfortable engaging across teams and business units to gather requirements and deliver solutions.
• Commercial Awareness: Strong understanding of banking products, customer behaviour, and business performance drivers.
• Adaptability: Able to manage multiple priorities and respond effectively to shifting business needs and technologies.
• Integrity & Compliance: Committed to data ethics, customer privacy, and adherence to regulatory standards.

• Bachelor's degree in Data Science, Actuarial, Statistics, Mathematics, Computer Science, Business Analytics, or a related field (required).

• 5–7 years of progressive experience in data analytics, business intelligence, or a closely related field.
• Demonstrated experience delivering dashboards, automated reports, and predictive models in a commercial setting.
• Solid understanding of data governance, data warehousing, and regulatory compliance in the financial sector.

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