What Technological Risks Jobs are in South Africa?

• Develop, validate, and deploy predictive models for credit risk, market risk, operational risk, and fraud detection.
• Apply machine learning techniques (e.g., regression, classification, clustering, deep learning) to solve complex business problems.
• Analyze large and diverse datasets to extract actionable insights and identify key risk drivers.
• Collaborate with risk management, business, and IT teams to define project requirements and deliver solutions.
• Perform data preprocessing, feature engineering, and model evaluation.
• Communicate complex analytical findings and recommendations to both technical and non-technical stakeholders.
• Stay current with the latest advancements in data science, machine learning, and risk analytics.
• Mentor junior data scientists and contribute to the team's technical development.
• Ensure the quality, integrity, and ethical use of data and models.
• Contribute to the development of data infrastructure and best practices.

• Ph.D. or Master's degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or a related discipline.
• Minimum of 5-7 years of hands-on experience as a Data Scientist, with a strong focus on risk analytics within the Banking & Finance industry.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas).
• Strong knowledge of statistical modeling, machine learning algorithms, and data mining techniques.
• Experience with SQL and working with large datasets from various sources.
• Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills.
• Ability to work effectively in a collaborative, hybrid environment.
• Experience within the financial sector in Nelspruit, Mpumalanga is advantageous.

• Lead a team of data scientists in the design, development, validation, and deployment of sophisticated risk models.
• Develop and implement advanced machine learning algorithms for credit scoring, fraud detection, and portfolio risk assessment.
• Utilize statistical techniques to analyze large, complex datasets, identify patterns, and derive actionable insights.
• Collaborate with business stakeholders, including risk management, product development, and IT teams, to understand needs and deliver data-driven solutions.
• Oversee the end-to-end model lifecycle management, including data acquisition, feature engineering, model training, validation, and monitoring.
• Ensure model robustness, accuracy, and compliance with regulatory requirements (e.g., Basel accords).
• Mentor junior data scientists, fostering a culture of innovation, learning, and high performance.
• Present complex findings and model results to both technical and non-technical audiences, including senior management.
• Stay abreast of the latest advancements in data science, machine learning, and financial risk management.
• Contribute to the strategic direction of the company's data science and risk analytics capabilities.

• Master's or Ph.D. in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field.
• Minimum of 6 years of experience in data science, with at least 2 years in a leadership or team management role.
• Proven experience in developing and deploying predictive models for financial risk management (credit, market, operational risk).
• Strong proficiency in programming languages such as Python or R, and experience with relevant data science libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Expertise in statistical modeling, machine learning techniques (e.g., regression, classification, clustering, deep learning), and data mining.
• Familiarity with SQL and experience working with large datasets and databases.
• Knowledge of financial regulations relevant to risk modeling is highly desirable.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain technical concepts to diverse audiences.
• Ability to thrive in a collaborative, hybrid work environment.

• Competitive salary with attractive performance-based incentives.
• Hybrid work arrangement offering flexibility and work-life balance.
• Comprehensive health and wellness benefits package.
• Generous contributions to a retirement savings fund.
• Opportunities for continuous learning, professional development, and attending industry conferences.
• Be part of a dynamic and innovative team shaping the future of financial risk management in Port Elizabeth .
• Access to cutting-edge technology and data infrastructure.

• Create Issued-for-Construction drawings and perform re-designs as required.
• Draught fire design drawings and piping layouts.
• Develop As-Built (red-line) drawings.
• Produce and issue working drawings.
• Perform hydraulic calculations.
• Prepare and issue cutting lists, layouts, and bills of materials.
• Coordinate with structural, electrical, and mechanical design teams.
• Draught fire sprinkler and suppression systems in line with NFPA and ASIB standards.
• Conduct material, dimensional, and weight limitation calculations.
• Communicate with engineers, site managers, and installation teams.
• Identify and resolve existing or potential design flaws.
• Review and redraft technical drawings in collaboration with relevant stakeholders.
• Ensure all final drawings and designs are compliant with engineering and manufacturing regulations.
• Conduct site visits as required.

• ASIB Certification will be advantageous.
• Strong working knowledge of Microsoft Excel and Word.
• A distinction in Mathematics will be beneficial.
• Experience in sales and estimating, including tender compilations and protocols, will be advantageous.
• Knowledge of ASIB rules and established customer relationships will be considered a benefit.

Our client is a prominent and highly respected insurance brokerage division based in Durban. Committed to maintaining the highest standards of governance and regulatory excellence, they are seeking a diligent and experienced Legal, Risk & Compliance Officer to oversee their compliance framework and manage risk effectively across both long-term and short-term insurance categories.

Requirements:

Qualifications: RE1 and RE5 Qualifications are mandatory. An LLB degree will be highly advantageous.

Experience: 5+ years of proven experience in compliance and risk management within the insurance industry (covering both long-term and short-term insurance categories).

Expertise: Practical experience in legal research and litigation processes.

Responsibilities:

Monitor regulatory developments, communicate updates to the business, and assist in implementing new requirements.

Ensure all employees and the company remain compliant with the Financial Advisory and Intermediary Services (FAIS) Act, the Financial Intelligence Centre (FIC) Act, and all other applicable legislation.

Communicate with insurers regarding any regulatory or legal queries, and facilitate responses to external insurer audits.

Ensure all company financial lines insurances and licenses are renewed timeously.

Further develop, enhance, and implement the internal compliance framework and business processes.

Identify operational/business risks and prepare comprehensive risk management reports.

Amend and update all compliance documentation, including policy schedules and disclosure notices.

Attend to necessary compliance checks in respect of policy renewals.

Oversee and manage FICA and FAIS reporting and monitoring.

Prepare internal compliance monitoring reports and calculate monthly compliance scores.

Review internal claims and underwriting correspondence to ensure alignment with legislative requirements.

Liaise directly with the FSCA and other regulatory bodies as necessary.

Draft, review, and negotiate business contracts, insurance contracts, and company policies.

Required Knowledge & Skills:

Excellent analytical and problem-solving skills.

Strong background in business policy drafting.

Proven risk identification and mitigation strategies.

Solid experience in contract drafting and negotiation.

Deep understanding of corporate governance and compliance management.

• 6+ Develop models to generate insights and support business decisions
• 6+ years applying statistical methods, machine learning, and domain knowledge to solve complex business problems
• Minimum 1 years knowledge of foundational Large Language Models and agentic AI
• 6+ years Python/R, SQL, notebooks, visualization tools (Power BI), experimentation frameworks

• Postgraduate qualification in a quantitative field (Statistics, Computer Science, Mathematics, Engineering) or similar qualification.
• Relevant cloud certification in Data Science or Machine Learning or Artificial Intelligence - mandatory

• As a Data Scientist, you will analyse and interpret complex data to uncover insights that drive business performance and strategic decision-making. Using Python, SQL, Google BigQuery, and Google Looker, you will develop reports, dashboards, and analytical solutions, while partnering with stakeholders to identify opportunities, solve business challenges, and support data-driven growth. You will also contribute to continuous improvement by exploring new trends, tools, and techniques in data science and analytics.

• 3+ years' experience as a Data Scientist, Data Analyst, or similar role.
• Strong proficiency in Python , SQL , Google BigQuery , and Google Looker
• Experience working within Google Cloud Platform (GCP)
• Strong analytical and problem-solving abilities with experience working with large datasets
• Experience in statistical analysis, data modelling, and business insights generation
• Proficiency in data visualisation and reporting tools.
• Advanced Microsoft Excel skills
• Strong communication skills with the ability to present insights to technical and non-technical stakeholders
• Experience within financial services, credit, fintech, or data-driven industries will be advantageous
• Understanding of data governance and data privacy principles is beneficial

• Bachelor or Masters Degree in Mathematics, Statistics, Computer Science, Data Science, Data Analytics, Information Systems or a related quantitative field