Fresh Jobs at Discovery Limited

Key Purpose

• Serve as the technical cornerstone of the AI Enablement team by building and maintaining production-grade Python systems, managing ML pipelines, and ensuring models operate reliably at scale. This role sets technical standards, mentors team members, and drives innovation through robust engineering practices.

Key outputs

The successful applicant will be responsible for but not limited to the following job functions:

Areas of responsibility may include but not limited to

• Architect and maintain high-performance Python code for AI/ML projects.
• Lead peer reviews and enforce best practices in software engineering.
• Design and manage ELT/ETL pipelines in MPP environments (for instance using Spark, Ray or similar).
• Oversee ML model lifecycle: deployment, monitoring, optimization.
• Implement automated monitoring and alerting for production models.
• Mentor junior developers and data scientists on coding standards.
• Collaborate with stakeholders to translate requirements into technical solutions.

Personal Attributes and Skills

The successful candidate would need to have the following competencies:

• Technical Leadership – Expert in Python and software architecture; sets high standards for code quality.
• Problem Solving – Ability to debug complex systems and deliver scalable solutions.
• Collaboration – Works effectively with data scientists, engineers, and business teams.
• Ownership Mindset – Takes responsibility for system resilience and performance.
• Continuous Learning – Stays current with emerging technologies and MLOps practices.

Education and Experience

The following requirements are Essential:

• 5+ years in Python development and software engineering best practices.
• Experience with CI/CD, Git, unit testing, and SOLID principles.
• Hands-on experience with MLOps tools (e.g. MLflow, Kubeflow, etc).
• Strong knowledge of cloud platforms (e.g. AWS, Azure, GCP).

The following requirements are advantageous:

• Experience with tools like Vertex AI, BigQuery, Cloud Composer.
• Exposure to large-scale data environments and distributed systems.
   

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Key Purpose

• The AI Lead is responsible for translating cutting-edge data science into robust, scalable production systems. This role leads a multidisciplinary team focused on the productionisation of machine learning and LLM models, ensuring operational excellence, technical innovation, and strategic alignment with business goals. Success in this position requires architecting and implementing production-grade systems that are scalable, maintainable, resilient, and integrated with existing production systems.

Key outputs

The successful applicant will be responsible for but not limited to the following job functions:

Areas of responsibility may include but not limited to

Team Leadership & Delivery Management

• Lead and mentor a cross-functional squad of engineers, developers, analysts, and data scientists.
• Drive agile delivery practices, ensuring timely and high-quality deployment of AI solutions.

Technical Strategy & Architecture

• Own the technical roadmap for AI productionisation, including MLOps, LLMOps, and scalable infrastructure.
• Oversee architectural decisions for model deployment, data pipelines, and cloud-native solutions.

Operational Excellence

• Implement monitoring, alerting, and incident response for AI systems in production.
• Champion best practices in CI/CD, testing, and observability for ML and LLM models.

Stakeholder Engagement

• Collaborate with data science teams to translate prototypes into production-ready applications.
• Liaise with platform and infrastructure teams to ensure seamless integration and scalability.

Strategic Impact

• Influence the velocity and reliability of AI delivery across the organisation.
• Represent the AI Enablement team in strategic forums and contribute to group-wide innovation.

Personal Attributes and Skills

The successful candidate would need to have the following competencies:

• Collaborative mentor with a natural inclination to share knowledge.
• Pragmatic and results-driven, focused on delivering robust solutions.
• Intellectually curious with a passion for technology and innovation.
• Excellent communicator, able to articulate complex technical ideas clearly.
• Ownership mindset with resilience and adaptability.

Education and Experience

The following requirements are Essential:

• Master’s degree in computer science, Engineering, or related field.
• 12+ years in software/data engineering or AI productionisation.
• Advanced proficiency in Python, SQL, cloud-native development, and MLOps/LLMOps tools.
• Experience with CI/CD, containerisation (Docker, Kubernetes), and infrastructure-as-code.

The following requirements are advantageous:

• Postgraduate qualification in AI, Data Science, or Systems Engineering.
• Familiarity with Vertex AI, BigQuery, Cloud Composer, Kubeflow.

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Key Purpose             

• The FAIS Centre of Excellence is a compliance function within Group Compliance that provides compliance oversight and advice to Discovery FESPs, key Individual and Representatives. The purpose of this role is to provide sound advice to FSPs, representatives and key individuals regarding legislation, regulation, industry standards, codes, guidelines and best practice protocols through compliance risk management principles, policies, processes and procedures.

Areas of responsibility

The successful candidate will be required, primarily, but not limited to:

• Advise management on implementing and maintaining an appropriate compliance framework which meets the compliance-related objectives of the business.
• Identify training and awareness needs.
• Build, develop and maintain strong cross-functional relationships with the key internal and external stakeholders to assess and anticipate emerging risk areas that involves the operations of key individuals, representatives, juristic representatives and franchises.
• Advising, representatives, juristic representatives and key individuals on suitable control frameworks to implement regulatory obligation Providing guidance into business processes, procedures and systems.
• Providing guidance into business processes, procedures and systems.
• Keep abreast of regulatory developments and changes in the financial services industry, with particular focus on FAIS and all subordinated legislation.
• Conduct onsite visits at key individuals, representatives and juristic representative offices to perform the following:
• Client files reviews
• Office assessment looking at compliance operational processes and POPIA requirements.
• Presentation on compliance updates i.e. Regulatory updates, compliance exposures, complaints, regulatory deadlines.
• Establish appropriate mechanisms to ensure effective oversight to:
• coordinate and drive compliance in the Distribution channel and assist management to implement or review compliance structures that will encourage a compliance culture.
• monitor and enforce effective control, governance and compliance standards.
• engage with key individuals, representatives, juristic representatives and franchises on any incidents and exposures and ensuring that these are dealt with in line with regulatory requirements.
• ensure policies, standards and frameworks are appropriate for the business.
• support the implementation of appropriate monitoring of compliance with regulatory requirements.
• provide comprehensive reports and feedback to senior management.
• Managing regulatory changes:
• analyse changes and evaluate the impact on business and communicate to business.
• providing guidance and support to business on the implementation of new and amended regulatory requirements.
• ensure timeous implementation of new and amended regulatory requirements.
• engage with business to draft comments on proposed legislation and amendments to Regulation.
• Manage ad hoc projects as may reasonably be assigned by management in line with regulatory and business needs.

Education and Experience

• 2 years’ of working experience in a financial services compliance role
• Relevant tertiary education
• Recognised compliance qualification from accredited institution
• Member of CISA, FPI would be advantageous.

Skills and Personal Attributes

• Knowledge of local (South African) legislation relating to financial services and able to interpret and apply legislation, including, but not limited to the following: FAIS, Protection of Personal Information Act, Insurance Act.
• Understanding of Compliance methodology, working knowledge of all elements comprising.
• Efficient time management skills, including quick turnaround time on quality work.
• Problem solving skills and conflict-management of situations in a constructive and professional manner.
• Ability to make rational judgements from the available information and analysis and provide considered and consistent advice.
• Communication, reporting and presentation skills.
• Ability to work as a team, understand the impact of decisions and be confident enough to raise concerns within the team and to senior management.
• Research ability and attention to detail.
• Detailed expertise in the operation and governance requirements of FSPs.
• Develop an effective network with business representatives and to build the necessary trust relationship with business representatives.
• Writes in a well-structured and logical way – must have ability to write and review compliance policies and draft compliance guidance notes and reports with detail required to inform the business of regulatory requirements and potential impacts.
• Able to work well under pressure.
• Efficient time management skills, including quick turnaround time on quality work.

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Key purpose

• Discovery is a high-performance organisation which prides itself in attracting the best talent. Our environment is always buzzing with energy as smart, motivated people challenge themselves to find the best way to do things. In addition to being passionate about working in this fast-paced organisation, the successful applicant will be responsible for data extraction, analyses, modelling and BI reporting within the Marketing Data Science Hub team.

Key outputs

• Perform analyses, provide insights, and build predictive models that will assist with sales, distribution, and general marketing analytics.
• Expand the suite of automated analytical/KPI reports used by clients of the Marketing Data Science Hub team (relating to lead volumes, call centre metrics, campaign performance etc.).
• Be an enabler of performance marketing, i.e. perform analyses, provide insights, and build predictive models that will assist with:
• Client segmentation and ideal client identification.
• Development and implementation of targeted marketing strategies.
• Optimisation of call centre operations.
• Digital marketing optimisation.
• Source and provide customised data to the business.
• Guide business stakeholders in what data to extract.
• Improve processes and databases where opportunities arise.
• Interpret and disseminate information via reports and publications.

Competencies

• Strong analytical and statistical modelling/machine learning skills.
• Skill in producing BI reports and working with BI software tools (big advantage).
• Above average ability to work with, analyse and report on data.
• Ability to source data from both structured and unstructured sources.
• Good communication skills and ability to build relationships with key stakeholders.
• Ability to work under pressure and in conditions of change.
• A team player who can work alone when required and without supervision.
• Ability to multi-task and to manage workload.
• Organized
• High level of attention to detail.
• Resilience, enthusiasm, energy and drive.
• Positive, can-do attitude.
• Ethical and able to maintain confidentiality and manage boundaries.
• Aligned to Discovery values and core purpose

Qualification and experience

• Honours degree (or higher) in statistics, actuarial sciences, computer science (or equivalent, relevant qualification)
• Knowledge of statistical packages (R, SAS, SPSS, Python etc.)
• Knowledge of BI reporting tools (Power BI, Tableau, QlikView)
• Experience in statistical and machine learning modelling techniques
• High level of computer literacy (advanced MS-Excel and SQL)
• 2+ years of work experience as a Data Analyst, Quantitative Analyst or Data Scientist