Information TechnologyFull-TimeSenior-level(6+ yrs)
Job Description
Role Overview
The Manager Business Performance at HF Group is responsible for driving data-driven decision-making across the organization. This role involves designing, developing, and maintaining analytical frameworks, dashboards, and performance reports to track business unit efficiency. The manager will leverage advanced analytics and machine learning to forecast customer behavior, mitigate risks, and optimize product profitability. Additionally, the role includes leading a team of analysts and ensuring data governance and quality across all analytical outputs.
Key Responsibilities
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.
Work closely with business units 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
Accurate, timely dashboards and performance reports delivered to business stakeholders.
Validated predictive models supporting lending, fraud detection, and risk management.
Customer segmentation and behavioural analyses informing marketing strategy.
Standardised KPIs and metrics for consistent performance tracking.
Maintenance of data quality and governance compliance records.
Requirements and Qualifications
Education: Bachelor's degree in Data Science, Actuarial Science, Statistics, Mathematics, Computer Science, Business Analytics, or a related field (Required).
Experience: 5–7 years of progressive experience in data analytics, business intelligence, or a closely related field.
Commercial Experience: Demonstrated experience delivering dashboards, automated reports, and predictive models in a commercial setting.
Sector Knowledge: Solid understanding of data governance, data warehousing, and regulatory compliance in the financial sector.
Technical Skills
Proficiency in Power BI or Tableau.
Strong command of SQL for data extraction and manipulation.
Proficiency in Python and/or R for statistical analysis and machine learning.
Experience with cloud platforms (AWS, Azure, or Google Cloud).
Familiarity with big data frameworks (Apache Spark, Kafka, or Hadoop) is an advantage.
Knowledge of KPI tracking methodologies and reporting automation.
