Legacy Reward Modelling Specialist

Are you excited about using data to shape the future of the Legacy Rewards Program and enhance learner engagement? Do you thrive on developing models and insights that optimize program performance, predict learner behaviour, and drive financial sustainability? Are you passionate about using analytics to inform strategic decision-making and improve how learners interact with rewards? If so, this might just be the role for you!

ABOUT ALX AFRICA

ALX Africa, a non-profit organisation under the ALX Foundation, is dedicated to unlocking the potential of Africa's digital future. Formerly part of Sand Tech Holdings, we've embarked on an independent journey to provide worldclass tech skills training and career acceleration programmes. Our mission is to bridge the digital divide, upskill and reskill talent, and create a generation of innovative leaders. By 2030, we aim to empower 2 million Africans to secure sustainable tech careers.

With hubs in 8 cities across Africa and counting, we provide safe access to quality learning and a dedicated network of expert instructors. Our innovative programmes equip learners with the practical skills and knowledge needed to succeed in today's rapidly evolving tech industry. Through a combination of rigorous coursework, industry partnerships, and hands-on projects, we prepare our students for in-demand roles in software engineering, data science, and cybersecurity.

We achieve this by:

• Providing young professionals with access to the most in-demand tech skills that will power the future.
• Empowering the next generation of technology innovators, entrepreneurs, and business leaders through challenging, real-world coursework.
• Building a lifelong, impactful community of tech professionals that support them at all stages of their career journey. 

 Visit our website www.alxafrica.com to learn more about our digital revolution.

ROLE SUMMARY

Legacy Rewards is responsible for driving key learner and alumni behaviors—such as persistence, graduation, career readiness, and sustained, financially sustainable engagement—across ALX programs.

As the Legacy Rewards Modelling Specialist, you will play a pivotal role in leveraging behavioral data analysis and predictive modelling to optimise program performance, engagement, and reward sustainability. Your work will be instrumental in refining points allocation models, forecasting redemption trends, and driving strategic decision-making through actionable insights.

Reporting to the Loyalty & Rewards Lead, you will own the development, testing, and continuous improvement of data models and algorithms that shape how Legacy Points are earned and redeemed. You will also work closely with the broader Legacy Rewards Team to support their data, insights, and reporting needs, including Reward Stock Forecasts, pilot evaluations, and performance tracking.

This role requires a self-driven, highly analytical professional with strong communication skills to translate complex data into clear, strategic recommendations that drive program innovation and financial sustainability.

KEY RESPONSIBILITIES

• Develop and refine data models and predictive analytics to assess learner behavior, engagement patterns, and points accumulation trends.
• Optimise points allocation algorithms to ensure fairness, engagement, and long-term financial sustainability.
• Build and maintain dashboards and reports tracking key program metrics such as points issuance, engagement trends, redemption rates, and financial impact.
• Monitor, track, and forecast reward budgets, working closely with the Loyalty & Rewards Lead to build the annual rewards budget and ensure cost-effective allocation of resources.
• Provide insights and data models to support reward partnerships, helping inform negotiations and secure sustainable, cost-effective reward offerings.
• Support the broader Legacy Rewards Team by providing insights and analysis on reward stock forecasting, pilot results, and operational reporting.
• Conduct audits and performance analysis to identify discrepancies, optimise forecasting accuracy, and refine redemption structures.
• Deliver actionable insights to inform program enhancements, reward optimisations, pilots, AB tests, and budget allocations.

You will collaborate with teams across Product, Marketing, Learning, Data, Engineering, Servicing, and Partnerships to implement and optimise learner engagement strategies, partnerships, points allocation and redemption models, and ensure rewards remain engaging and financially sustainable through data-driven insights. You will also work closely with the Loyalty & Rewards Lead to ensure analytics and predictive modelling drive continuous improvements, program scalability, and long-term sustainability while aligning with key program priorities.

The position requires:

• Advanced analytics and predictive modelling expertise to support data-driven program optimisation.
• Proficiency in behavioral data analysis to improve engagement and refine points allocation models.
• Experience in data visualisation and reporting tools to present clear, actionable insights.
• Strong communication skills to translate complex data into meaningful recommendations for stakeholders.
• A proactive, self-driven approach with the ability to work independently and collaboratively across teams.
• High attention to detail and commitment to data integrity to ensure fair and accurate points allocation.
• Ability to work with multiple stakeholders, supporting Rewards Team needs for data-driven decision-making and program performance tracking.

SPECIFIC RESPONSIBILITIES

• Data-Driven Program Optimisation & Insights:
  • Develop and refine data models and predictive analytics to assess learner behavior, engagement patterns, and points accumulation trends.
  • Optimise points allocation algorithms to ensure fairness, engagement, and long-term financial sustainability.
  • Provide actionable insights to improve program performance, engagement, forecast redemption trends, and inform reward strategies.
  • Conduct data integrity audits to ensure all points transactions comply with program policies, internal controls, and regulatory standards.
• Reward Budgeting, Forecasting & Financial Modelling:
  • Monitor, track, and forecast reward budgets to support financial planning and sustainability of the program.
  • Conduct financial modelling and scenario analysis to assess the long-term sustainability of reward structures and points economy.
  • Collaborate with the Loyalty & Rewards Lead to analyse the financial impact of points allocation and reward redemptions and adjust strategies accordingly.
• Points Allocation & Algorithm Optimisation:
  • Design, implement, and continuously improve points allocation models to ensure accuracy, engagement, and alignment with program goals.
  • Automate and streamline points calculations by working closely with Data and Engineering teams, reducing manual intervention and improving reliability.
  • Conduct regular audits to identify and correct inconsistencies in points allocation.
• Performance Reporting & Data Integrity:
  • Build and maintain dashboards tracking key program metrics such as points issuance, engagement trends, redemption rates, and financial impact.
  • Provide regular reports to inform program decisions, ensuring that insights drive engagement strategies and financial sustainability.
  • Support the Legacy Rewards Team with data, forecasting, and reporting needs
• Support for Pilots, AB Testing & Data-Driven Decision-Making:
  • Collaborate with the Loyalty & Rewards team to provide data-driven insights that inform pilots and AB testing of new reward structures, points actions, partnerships, and engagement strategies.
  • Analyse AB tests, engagement strategies, and pilot results, measuring effectiveness, identifying trends, and delivering clear, actionable recommendations to support decision-making on whether to scale or refine initiatives.
• Insights to Inform Reward Partnerships & Negotiations:
  • Support the Partnerships team with data-driven insights on reward performance, cost efficiency, and demand trends.
  • Analyse learner redemption behavior to determine which rewards drive engagement and satisfaction, helping to inform negotiations with partners.
  • Provide data-backed recommendations to ensure reward offerings are cost-effective, engaging, and aligned with program goals.
• Collaboration & Cross-Functional Alignment:
  • Work closely with teams across Product, Marketing, Learning, Data, Engineering, Servicing, and Partnerships to ensure analytics and predictive modelling drive program improvements.
  • Align closely with the Loyalty & Rewards Lead to ensure modelling efforts contribute to sustainability, scalability, and learner engagement goals.
• Cultivate and Manage Relationships:
  • Build strong relationships with internal stakeholders to ensure data-driven decision-making supports program sustainability and strategic objectives.
  • Collaborate with cross-functional teams (e.g., Data, Engineering, Finance, Product, and Partnerships) to provide insights that enhance reward structures, points allocation, and cost-effectiveness.

KEY PERFORMANCE INDICATORS

• Data Accuracy & Reporting Efficiency: Ensure 95%+ accuracy in program reports, delivering timely insights to optimise decision-making.
• Points Allocation & Engagement Optimisation: Improve points allocation models to increase engagement and reduce discrepancies, measured by successful allocation rates and learner interaction with reward actions.
• Predictive Modelling & Reward Forecasting: Develop 85%+ accurate models for learner behaviour, reward demand, and redemption trends to support program sustainability and engagement.
• Reward Budgeting & Cost Control: Align reward spend with budget targets, ensuring forecast variance remains within 5%, while optimising stock availability and minimising wastage.
• Data Integrity & Compliance: Maintain minimal discrepancies in data audits, ensuring all transactions align with program policies and financial controls.
• Stakeholder Impact & Strategic Insights: Provide data-backed recommendations that enhance reward partnerships, engagement strategies, and program scalability, measured by successful implementation of insights and positive stakeholder feedback.

SKILL REQUIREMENTS - ESSENTIAL

• Advanced Analytics & Predictive Modelling: Strong proficiency in statistical analysis, data modelling, and predictive analytics to optimise reward structures, points allocation, and program sustainability.
• Data Accuracy & Integrity: Detail-oriented with a commitment to maintaining high data integrity, ensuring all reporting, forecasting, and points calculations are accurate and reliable.
• Strategic Problem-Solving:  Ability to identify trends, detect inefficiencies, and propose data-driven solutions that improve program performance and financial sustainability.
• Financial Modelling & Reward Budgeting: Experience in forecasting reward budgets, tracking spend variance, and aligning financial models with program sustainability and engagement goals.
• Collaboration & Stakeholder Engagement: Proven ability to work cross-functionally with Data, Finance, Product, Engineering, and Partnerships teams to translate insights into actionable program improvements.
• Communication & Business Impact: Ability to translate complex data insights into clear, strategic recommendations, supporting decision-making at all levels of the organisation.
• Self-Driven & Adaptable: Highly self-motivated, able to take ownership of analytics and forecasting, while ensuring alignment with program goals and evolving business needs.

PERSON SPECIFICATION/ATTRIBUTES

• Courage: Willingness to speak up, challenge the status quo, and embrace new challenges.
• Humility: Openness to learning, seeking help when needed, and a focus on serving others.
• Adventure: A passion for setting ambitious goals, tackling difficult tasks, and finding joy in the journey.
• Initiative: Proactive problem-solving, a sense of ownership, and a willingness to go above and beyond.
• Resilience: The ability to bounce back from setbacks, persevere through challenges, and emerge stronger.