Manager Business Performance

About HF Group Plc

HF Group Plc is an integrated financial solutions provider registered as a non–operating holding company. It is regulated by the Central Bank of Kenya (CBK) and the Capital Markets Authority (CMA). The Group is a public limited company with interests in Banking, Property, and Insurance, and is listed at the Nairobi Securities Exchange. For more information on our banking, property and insurance solutions, please visit www.hfgroup.co.ke. The Group has 4 main entities: HFC – Full-Service Banking, HF Development & Investments (HFDI) – Property/Real Estate Solutions, HF Bancassurance Intermediary (HFBI) – Insurance Solutions, and HF Foundation – ESG/Sustainability.

On the back of a strong growth trajectory and in a bid to power the business, HF Group Plc is looking to recruit a dynamic and results-oriented Manager Business Performance.

About the Role

The Manager, Business Performance, will enable the Data & Analytics division and its business partners to develop, implement, and continuously improve analytics frameworks, performance reporting tools, and predictive models that track the progress of business strategies and initiatives. The role is therefore critical in ensuring that the banking group makes confident, data-driven decisions, fosters stronger cross-functional collaboration, exercises prudence in its resource and cost planning, and builds the agility to respond to evolving market and customer dynamics.

Principle Accountabilities

Analytics & Reporting

• 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.

Performance Monitoring

• 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.

Advanced Analytics & Predictive Modelling

• 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).

Customer Insights & Personalisation

• 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.

Data Governance & Quality

• 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.

Cross-Functional Collaboration & Stakeholder Engagement

• 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.

Team Leadership & Capability Development

• 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.

Principal Outputs for this Role

• 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.

Key Competencies and Skills

Technical Competencies

• 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.

General Competencies

• 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.

Minimum Qualifications, Knowledge And Experience

• 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.

Key skills/competency

• Business Performance Analysis
• Data Visualization (Power BI, Tableau)
• SQL
• Python/R for Analytics
• Predictive Modeling
• Machine Learning
• Data Governance
• Stakeholder Management
• Financial Sector Data
• Business Intelligence