About this role
Discovery – Insure Process Intelligence Engineer About Discovery Discovery’s core purpose is to make people healthier and to enhance and protect their lives. We seek out and invest in exceptional individuals who understand and support our core purpose, and whose own values align with those of Discovery. Our fast-paced and dynamic environment enables smart, self-driven people to be their best. As global thought leaders, Discovery is passionate about innovating in order to not only achieve financial success, but to ignite positive and meaningful change within our society. About Discovery Insure Discovery Insure is committed to creating a nation of great drivers through our innovative Shared-value Insurance model. Discovery Insure is South Africa’s fastest growing short-term insurance company with comprehensive products that provide protection against current and emerging risks facing clients in the motor and home insurance sectors. Vitality Drive, an internationally-recognised and award-winning programme, is a key differentiator in the market that incentivises and rewards clients for driving well. The Vitality Drive programme has been scaled to local and international markets which now include Europe and the Middle East. The company employs over 1 000 people who are committed to putting our customers and financial advisers first by providing unique and innovative solutions and cover. Key Purpose The Process Intelligence Engineer is a specialist who uses data to reveal how work is actually performed across the business and turns that insight into AI and automation solutions that deliver measurable value. The role combines task mining (capturing desktop activity such as clicks, keystrokes and application switching) with process mining (reconstructing end-to-end processes from system event logs) and hands-on discovery, to build an objective view of each process: its variants, bottlenecks, rework and the hidden manual effort that sits outside core systems. From this, the engineer sizes and prioritises the opportunities worth automating and designs the right intervention: AI agents, RPA, integrations or process standardisation. Areas of responsibility may include but are not limited to: Project Ownership and Delivery: Own each automation project end to end, from discovery and problem identification through scoping, solution design, build, testing, go-live and business adoption, working hand in hand with the squad's Automation Engineer, Systems, data engineering and business stakeholders. Process and Task Discovery: Deploy task mining and process mining, supported by workshops, interviews and floor observation, to capture how work really happens, including the hidden manual effort, workarounds and rework that sit outside core systems. Event Data Modelling and Process Analysis: Extract and model event-log and desktop activity data, reconstruct current-state processes, and analyse variants, bottlenecks, conformance gaps and root causes. Build current- and future-state process maps (e.g. BPMN) and standardise processes before they are automated. Opportunity Sizing and Prioritisation: Quantify the effort, cost, cycle time and error impact of each opportunity, build business cases with clear baselines, and recommend priorities into the automation portfolio managed by the Process Intelligence Lead. Solution and AI Agent Design: Design the right intervention for each problem, whether AI agents, LLM-enabled document and decision steps, RPA, system integrations or process redesign. Prototype AI agent components and produce clear specifications that the Automation Engineer builds against on the enterprise stack where appropriate. Value Realisation and Process Monitoring: Define KPIs and baselines up front, track benefits after go-live (capacity released, cycle time, quality and error rates), and use continuous process monitoring to confirm that value is sustained and to inform the value gates that govern squad expansion. Stakeholder Engagement and Change: Act as the trusted partner to operational leaders and teams, facilitate discovery and design workshops, communicate findings clearly to senior stakeholders, and guide teams through the process and role changes that automation brings. Governance and Industry Insights: Ensure task mining, data handling and AI solutions meet POPIA, privacy impact assessment and AI governance requirements, and track developments in process intelligence, task mining and agentic AI to evolve the squad's toolkit and repeatable delivery model. Knowledge and Skills: SQL, relational databases and event-log data; Python and/or Power BI for analysis. Process mapping (BPMN) and root cause, variant and bottleneck analysis. Process or task mining platforms. (Preferred) Working knowledge of LLMs, AI agents, RPA, integrations and Azure services. (Preferred) Education and Experience Education: Matric Bachelor's degree in Industrial Engineering, Information Systems, Computer Science, Data Science, Applied Mathematics, Statistics, Actuarial Science or a similar quantitative or engineering field. Honours or Master's degree in a relevant field. (Preferred) Experience: At least 5 years in process improvement, process mining, business analysis, intelligent automation or operations analytics. A track record of owning improvement or automation projects from discovery through to measured benefits. Hands-on analysis of operational or event-log data (SQL) to identify and size opportunities. Hands-on experience with a process or task mining platform (e.g. Celonis, Soroco, Mimica etc.). (Preferred) Experience designing AI agent, LLM or RPA solutions, ideally with a consulting background. (Preferred) EMPLOYMENT EQUITY The Company’s approved Employment Equity Plan and Targets will be considered as part of the recruitment process. As an Equal Opportunities employer, we actively encourage and welcome people with various disabilities to apply.