The posting
Role Purpose
The Head of Data Analytics leads GoTyme Bank's business-facing data science capability across Marketing, Fraud, AML, Customer Experience, Distribution and Partnerships. You will turn company and functional priorities into a clear analytics roadmap, lead and develop a team of data scientists and senior data scientists, and ensure that the team's work changes decisions and improves measurable business outcomes.
This is a senior people and delivery leadership role with strong technical credibility. You will move the function from reactive request fulfilment towards proactive insight, experimentation and responsible use of advanced analytics and AI. You will work closely with Reporting and Insights, Data Governance, Data Engineering, Finance, Risk, Product and Lending Analytics so that decision makers receive trusted, timely and well-governed analysis.
Key Responsibilities
- Analytics Strategy and Business Impact
- Set and own the data analytics strategy and roadmap for the functions in scope, aligned to GoTyme Bank's company priorities and measurable business outcomes.
- Direct proactive analysis across customer acquisition, activation, engagement, segmentation, revenue, fraud prevention, AML effectiveness, customer experience, distribution performance and partner value.
- Frame the right business questions, identify opportunities before they become requests, and ensure insights are translated into decisions, actions and measurable impact.
- Establish clear success measures for major analytics initiatives and track whether recommendations are adopted and deliver the intended result.
- People Leadership and Capability
- Act as the primary line manager for data scientists and senior data scientists within the function, owning performance, development and day-to-day effectiveness.
- Recruit, onboard, coach and retain strong analytical talent; set clear expectations and provide regular, honest and developmental feedback.
- Build succession and capability plans, create opportunities for team members to take on greater responsibility, and address performance or capability gaps early.
- Create a team environment where people collaborate across domains, share knowledge, raise risks openly and maintain high standards without losing pace.
- Prioritisation Planning and Delivery
- Run a transparent intake and prioritisation process so that analytical capacity is directed to the highest-value work across the functions in scope.
- Maintain a visible roadmap, stakeholder service levels and a regular operating cadence covering delivery, impact, capacity, risks and dependencies.
- Own the quality and timeliness of the team's output; resolve blockers, coordinate cross-team dependencies and escalate trade-offs early when capacity or priorities conflict.
- Clarify ownership and hand-offs with Reporting and Insights, Data Governance, Data Engineering and Lending Analytics to avoid duplicated work or gaps in delivery.
- Stakeholder Leadership
- Act as the senior analytics partner for Marketing, Fraud, AML, Customer Experience, Distribution and Partnerships, building trusted relationships with functional leaders and their teams.
- Communicate analytical strategy, evidence, trade-offs and recommendations clearly to executive, commercial, risk and technical audiences.
- Represent Data Analytics in relevant governance, planning and performance forums, ensuring that evidence is used in material decisions.
- Challenge assumptions constructively, establish common definitions and help stakeholders distinguish useful analysis from activity that will not change a decision.
- Analytical Standards Experimentation and Innovation
- Set consistent standards for analytical design, SQL and Python development, peer review, documentation, reproducibility, quality assurance and communication of results.
- Build disciplined test-and-learn practices for campaigns, customer journeys, fraud controls, segmentation, channel interventions and partner initiatives.
- Apply advanced analytics, machine learning and generative AI where they can improve decisions, turnaround time or efficiency, with clear measures of value and appropriate human oversight.
- Partner with platform, engineering and reporting teams to create reusable data products, scalable analytical assets and well-governed self-service capabilities.
- Governance Risk and Compliance
- Ensure that the function complies with data governance, privacy, information security, model governance and regulatory requirements, including appropriate access controls and audit trails.
- Maintain documented review and monitoring processes for analytical outputs used in customer, risk, executive or regulatory decisions.
- Identify and escalate material data quality, bias, control or interpretation risks, and ensure agreed remediation is completed.
- Support audit and regulatory requests relevant to the function and ensure that all team members complete required compliance training.
Measures of Success
- A clear, transparent roadmap directs capacity to the company's highest-value priorities, with delivery risks and trade-offs surfaced early.
- Business leaders receive proactive insights and use them to improve acquisition, activation, engagement, revenue, loss prevention, control effectiveness, customer experience, distribution and partner performance.
- Analytics initiatives have defined measures of success, and the function can demonstrate adoption, impact and lessons from unsuccessful tests.
- The team is well led, appropriately staffed and growing in capability, with clear goals, strong retention and credible succession plans.
- Outputs are reliable, documented, reproducible and compliant, with material audit or control issues addressed promptly.
Requirements
Requirements
Experience
- At least 10 years of experience in data science, business analytics or a related quantitative field, including substantial people leadership responsibility.
- Demonstrated success leading senior analytical talent and delivering high-quality work through teams rather than relying on personal contribution alone.
- Track record of using analytics to improve commercial, customer, operational or risk outcomes in a complex organisation.
- Experience managing a portfolio of competing work and influencing senior stakeholders when priorities, capacity or evidence are contested.
Qualifications
- Bachelor's degree in statistics, mathematics, data science, computer science, engineering, econometrics or a related quantitative discipline.
- Postgraduate qualification advantageous.
Skills
- Strong technical grounding in statistics, experimentation, predictive modelling and data science, with current proficiency in SQL and Python sufficient to review and guide the team's work.
- Commercial judgement and the ability to connect analytical work to customer, revenue, cost, risk, control and service outcomes.
- Strong people leadership across performance management, coaching, feedback, hiring and career development.
- Clear, structured communication across technical and non-technical audiences, including executive-level recommendations and difficult stakeholder conversations.
- Strong prioritisation, portfolio planning and delivery management, with the ability to make transparent decisions under ambiguity and capacity constraints.
- Sound understanding of data quality, privacy, analytical governance and the controls required in a regulated environment.
Nice to Have
- Experience in retail banking, fintech or another regulated consumer business.
- Domain experience in more than one of marketing analytics, customer analytics, fraud, financial crime, distribution analytics or partner data.
- Experience with modern cloud analytics platforms such as Databricks and with team-based development practices including Git and code review.
- Experience with analytical governance, model risk, regulatory reporting, audit remediation or privacy requirements such as POPIA.
- Experience leading teams through organisational change, rapid growth or a shift from reactive requests to proactive analytics.
Personal Attributes
- People-first leader who invests in the growth, performance and wellbeing of the team.
- Proactive and commercially curious; looks for important questions and opportunities rather than waiting for a request.
- Pragmatic and evidence-led; balances analytical rigour with pace, capacity and business need.
- Direct and fair; gives clear feedback, handles difficult conversations and makes trade-offs visible.
- Calm and dependable under pressure, providing structure and direction when priorities are ambiguous or changing.
- Collaborative across functions and willing to challenge constructively when the evidence requires it.
Benefits
Our Benefits Include: Comprehensive Group Life Cover
- Life Cover
- Funeral Cover
- Global Education Protector
- Disability Cover (incl. Contribution Protector)
- Severe Illness Benefit
Healthcare That Works for You
- Full company contribution to Health Insurance for eligible employees.
- Partial company contribution to Medical Aid options for eligible employees.
Plan for Your Future
- Access to a Retirement Annuity, with convenient payroll deductions to help you save for retirement while benefiting from applicable tax advantages.
Other benefits include:
- EAP support (counselling, financial and legal for you and anyone financially dependent on you).
- Competitive, industry-benchmarked salaries.
- Non-guaranteed performance bonuses.
- Access to company shares (T's & C's apply).
- Wellness days.
- Social clubs.
- On-site barista.
