195 Analysts jobs in Gauteng

Not for First Time Job Seeker

Important:
This role requires all 12 listed skills.

Please ensure your CV clearly reflects each of these with traceable experience and references. Candidates missing any of the required skills will not be considered.

JOB ROLE - DATA SCIENCE/ AI/ML Engineers:-

Educational qualifications

• Bachelor's degree in data science, Statistics, Mathematics, Computer Science, or a related quantitative field.
• Master's or PhD in Machine Learning, Applied Mathematics, Econometrics, or AI (strongly preferred).

SKILLS:

Machine learning engineering

Azure databricks

Business acumen

Python

SQL

Version control and collaboration tools (git, azure repo)

Strong communication with non-technical stakeholders

Cloud platform knowledge (azure)

Model deployment (CI/CD pipelines, model monitoring)

Understanding of rag pipelines and autonomous agents

Feature and ml data engineering (advanced big data wrangling)

Understanding of project management and agile methodologies

Relevant experience

• 8–12 years of experience in data science, machine learning, or advanced analytics roles, with at least 3 years in a leadership or managerial capacity.
• Proven delivery of AI/ML models in production environments—preferably in Fintech, Banking, or Telecoms.
• Experience translating complex data science solutions into measurable business outcomes (e.g., credit scoring, fraud detection, churn prediction).
• Exposure to cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, GCP Vertex AI)."

Required certifications

Preferred: TensorFlow, AWS ML Speciality, Microsoft AI Fundamentals

Key responsibilities

• Lead and scale a high-performing team of data scientists and ML engineers.
• Define and execute the data science roadmap, aligned to business priorities and monetisation opportunities.
• Oversee the end-to-end model lifecycle—from ideation, exploration, development, validation, to monitoring.
• Partner with Product, Risk, and Engineering to integrate models into digital and operational channels.
• Establish standards for model governance, explainability, and ethical AI practices.
• Drive innovation by exploring emerging techniques in generative AI, reinforcement learning, and real-time scoring.

Work location

Hybrid

Contract Position

THE WORK
: Join our dynamic team and embark on a journey where you will be empowered to perform independently and become an SME. Required active participation/contribution in team discussions and contribute in providing solutions to work related problems. Let's create a brighter future together

Use existing research methods and develop new approaches to discover anthropological, ethnographical and sociological insights.

Develop brand tracking systems and convert data into relevant KPI dashboards.

Utilize analytical methodologies, mathematical modeling or optimization techniques to develop intellectual property.

BONUS POINTS IF YOU HAVE:

Advanced proficiency in Generative Design

Advanced proficiency in Machine Learning

HERE'S WHAT YOU WILL NEED:
Expert proficiency in Data Science.

Advanced proficiency in Data Analytics.

A minimum of 1 year of experience in relevant related skills.

Bachelor's Degree in relevant field of studies

BONUS POINTS IF YOU HAVE:
Advanced proficiency in Generative Design

Advanced proficiency in Machine Learning

Job Description

The Pricing Manager will lead strategic pricing for Transact interest and facility fees, driving revenue and profitability through data‑driven decision making. This role implements Analytics standards across assigned business units and converts data into monetisation opportunities by developing and deploying advanced mathematical models and commercial frameworks. The Pricing Manager uncovers hidden patterns and associations in customer and transaction data to shape pricing strategy, optimise channel design, and predict client behavior for improved product performance and customer outcomes.

• Ensure adoption and localization of appropriate model building policies, standards, frameworks, and governance process and integration of business modelling and analytics value chain.
• Establish goals and strategies for area of accountability in collaboration with senior data analytics management.
• Ensure ethical usage of information that complies to restrictions applied for privacy and sensitivity classification.
• Understand and ensure implementation and adherence to Privacy business requirements, legislation and policy.
• Ensure reporting of any Information Privacy Incidents and drive resolution of Privacy and Protection Audit.
• Findings, Complaints, Incidents, Investigations and Privacy and Protection Assessments.
• Provide and use data and analytic insights to improve customer experience through a better understanding of the customers context to identify monetization opportunities.
• Manage analytics team in the creation of high-quality analyses for all functions of the business, across area of accountability.
• Create tactical plans for achievement of outputs / deliverables in collaboration with business stakeholders to understand information requirements for strategy delivery and define metrics that track performance.
• Drive team performance of analytics solutions; drive and enhance data systems and streamline business processes to impact overall business results while keeping costs in check.
• Analyse available data to identify information commercialization opportunities that have not been explored to address business needs and revenue options.
• Ensure analytics productionization in the approved FirstRand architecture by translating technical data information into practical business information that addresses identified needs.
• Analyse information requirements, availability and quality of data to feed into Data and information management function and forums for resolution.
• Oversee the appropriate manipulation and analysis of data for to meet needs of the business for the purpose of future work and to ensure high information-quality and reliability across the business.
• Integrate analytics into operational processes to improve efficiency and client experience.
• Ensure development of core analytical capabilities or model libraries using advanced statistical, quantitative or econometric techniques.
• Manage overall project dependencies management and long-term prioritization of the business's overall analytical needs and opportunities.
• Serve as SME for analytics applying own understanding of the operations of the business product or service.
• Define the business questions for Business unit that need be answered; define appropriate analytics models in addition to identifying and readying relevant data sources for analysis.
• Address business problems and opportunities through robust underlying analytics.
• Translate business requirements into tangible solutions or models utilizing own understanding of business value and interrelated nature of projects, models and processes.
• Ensure accurate development and application of analytical algorithms and methods to build, test and implement advanced mathematical models and analytical solutions that address business problem, opportunities and improve business outcomes i.e. reduced risk and costs, increased profitability, optimized efficiency and to facilitate strategic decision making.
• Provide requirements to Business Information.
• Management Function as Supplier or Owner of Data to ensure data is prepared for consumption as an organizational asset.
• Create team tactical plans for achievement of outputs or deliverables in collaboration with Technology stakeholders to ensure the effective implementation of analytical solutions and models to support business requirements.
• Ensure governance and compliance rules are followed in application and implementation of predictive models to enable the business to manage risk.
• Maintain ownership and oversee the implementation of models.
• Monitor output and accuracy of models.
• Ensure the documentation and auditing of relevant models, projects and processes.
• Provide input into business strategies through data analysis that proactively improve efficiency, identify risks, save costs and drive innovation.
• Lead business through efforts that drive business performance and potential by using the existent and new data sources and techniques.
• Enable business unit to understand its own health, finds growth levers, and identify opportunities for optimization.
• Create new data-driven approaches for the purpose of generating business insights through data analytics, information visualization and addressing unanswered business issues in a proactive manner.
• Ensure validation and interpretation of analytical results and creation of reports and presentations for data analytics management, departmental heads/management, and relevant stakeholders.
• Collaborate with numerous departments across the business to assist in the proper use of data that ensure delivery of desired operational results.
• Model and drive a data driven culture that values data as an asset with business value.
• Lead relevant change and communications functions to drive functional maturity.
• Manage people by executing management responsibilities and create an environment that encourages employee growth and performance excellence.
• Prevent wastage and identify process improvements to contain and reduce costs.
• Take all necessary actions to ensure compliance with relevant statutory, legislative, policy and governance requirements in area of accountability.
• Ensure implementation of relevant policies, governance and practice standards across the business.
• Maintain expert knowledge on relevant legislative amendments, industry best practices and business's internal compliance procedures and requirements.
• Ensure compliance is adopted in terms of systems and procedures as laid out by business.
• Implement and provide input into the development of governance and compliance procedures and processes within area of specialization and identify risks.
• Build relationships that allow for the managing of expectations; the sharing of knowledge and diverse insights; and the creation of buy-in.

Additional requirements

• Relevant BSC Degree / Actuarial Science
• Minimum of 5 years' experience in a Data Science role
• Relevant Pricing Experience
• Experience Managing a team

Additional requirementEngage in cross-functional relationships to obtain and to provide work support

Job Details

Take note that applications will not be accepted on the below date and onwards, kindly submit applications ahead of the closing date indicated below.

23/10/25

All appointments will be made in line with FirstRand Group's Employment Equity plan. The Bank supports the recruitment and advancement of individuals with disabilities. In order for us to fulfill this purpose, candidates can disclose their disability information on a voluntary basis. The Bank will keep this information confidential unless we are required by law to disclose this information to other parties.

Who are we?
We made Miway to change the way insurance works, to make it work your way, protecting what matters to you and making life a whole lot easier.

Why Miway?We know what it's like to be in an early morning accident on the way to work, to watch helplessly as water floods your business premises, or have your most precious possessions stolen, to lose a truckload of costly stock, or be stranded a long way from home.

So, we created products that put you first, that help you get back on your feet, that make a difference when you're down and dealing with a loss. That's insurance the way it should be. Insurance your way.

That's Miway.You may want to be part of that. Insurance the way it should be. Built around you.It's about you - not about us.

Why Join Us?
This is a rare opportunity to lead at the frontier of actuarial innovation - where data science, machine learning, and software engineering create real-world impact. As Data Science Manager: Telemetry Solutions, you'll help shape the future of insurance.

• Lead actuarial and data science initiatives across telematics, claims, and operational intelligence.
• Work with rich, real-time datasets from connected vehicles and IoT platforms to unlock insights and build predictive systems.
• Collaborate with cross-functional teams - including product, development, and claims - to integrate analytics into key decision-making processes.
• Apply and grow your technical skills across AI, machine learning, and production-grade systems in a dynamic environment.
• Join a forward-looking team that values innovation, ownership, and continuous learning.

If you're technically strong, strategically curious, and passionate about using data science to tackle bold, modern challenges - this is your opportunity to lead the change.

What will you do?
The Data Science Manager: Telemetry Solutions is a future-focused leadership role that bridges actuarial science, data science, machine learning, and engineering. You will lead a multidisciplinary team that leverages telematics and alternative data to deliver intelligent solutions across usage-based insurance (UBI), claims innovation, product development, and dynamic risk assessment.

This role offers a unique opportunity to operate at the intersection of data, strategy, and technology - driving meaningful transformation in how insurance products are developed, risks are understood, and operations are optimised.

Key Responsibilities

• Architect and deploy scalable, real-time systems for ingesting, processing, and analysing high-frequency vehicle sensor and telemetry data.
• Develop and maintain robust APIs and automation tools in Python and C# to support internal platforms and customer-facing applications.
• Oversee the creation and deployment of AI models - including computer vision and large language models (LLMs) - to enhance claims automation and document intelligence.
• Champion innovation within the actuarial domain by blending traditional methodologies with modern MLOps, software engineering, and streaming analytics.
• Manage end-to-end machine learning pipelines using tools like MLflow, ensuring reproducibility, governance, and performance monitoring.
• Collaborate closely with Product, IT, Data Engineering, and Claims teams to embed intelligent analytics into core business processes and customer experiences.
• Mentor and grow a high-performing team of data scientists, and software engineers.
• Provide technical insight and data-driven narratives to support strategic decision-making through dashboards, models, and actuarial reporting.

Qualifications

• Degree in Actuarial Science, Data Science, Statistics, Computer Science, or a related field (Honours or Master's preferred).

Experience

• Minimum of 5 years' experience in data science, or data engineering roles, preferably in a telematics-driven insurance environment.
• Proficient in Python and C#, with a solid foundation in object-oriented programming and API development.
• Advanced SQL skills, including data processing, database management, and query optimisation (Essential).
• Practical experience using Git for version control and collaboration(Essential).
• Hands-on experience with machine learning libraries and frameworks such as XGBoost, spaCy, Hugging Face, TensorFlow, or PyTorch.
• Proven ability to deploy and monitor models using MLflow and related MLOps tools.
• Experience with large-scale datasets, ideally from IoT or telematics sources.
• Working knowledge of Docker for containerisation (Intermediate to Advanced – Advantageous).
• Exposure to messaging systems such as RabbitMQ (Advantageous).
• Strong understanding of software engineering principles, including object-oriented design and clean code practices.
• Solid business acumen with the ability to translate technical work into strategic outcomes.
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Demonstrated leadership experience and a passion for mentoring cross- functional teams.
• Strong analytical and problem-solving skills, with the ability to extract insights from high-volume, high-dimensional data

Knowledge And Skills
Actuarial Problem Solving

Issues management

Business knowledge

Business analysis

Personal Attributes
Self-development - Contributing independently

Interpersonal savvy - Contributing independently

Nimble learning - Contributing independently

Tech savvy - Contributing independently

Core Competencies
Cultivates innovation - Contributing independently

Customer focus - Contributing independently

Drives results - Contributing independently

Collaborates - Contributing independently

Being resilient - Contributing independently

Build a successful career with us
We're all about building strong, lasting relationships with our employees. We know that you have hopes for your future – your career, your personal development and of achieving great things. We pride ourselves in helping our employees to realise their worth. Through its five business clusters – Sanlam Fintech, Sanlam Life and Savings, Sanlam Investment Group, Sanlam Allianz, Santam, as well as MiWay and the Group Office – the group provides many opportunities for growth and development.

Turnaround time
The shortlisting process will only start once the application due date has been reached. The time taken to complete this process will depend on how far you progress and the availability of managers.

Deadline to apply: 19 September 2025.
Our commitment to transformation
At MiWay we believe in cultivating a positive and dynamic working environment that gives you freedom and opportunity to succeed. MiWay is committed to transformation and embracing diversity. This is what drives us to achieve a multicultural workplace with employment equity as a key goal to create an inclusive workforce, reflective of the demographics of our society.

We’re turning data into intelligent, actionable insights.

We create predictive, AI-driven systems that empower smarter decisions, improve customer experiences, and unlock growth opportunities.

Currently searching for a Data Science and AI Lead with AWS Cloud experience and a passion for innovation.

No dusty cubicles. Just smart humans building models that make a real business impact.

Requirements:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, or related field
• 10+ years’ experience in Data Science, AI, or ML roles
• 3+ years plus in a leadership role
• Experience deploying ML models in production using AWS (SageMaker, Redshift ML, Glue, Lambda)
• Proficiency in Python (pandas, scikit-learn, TensorFlow, PyTorch) and SQL
• Knowledge of predictive analytics, NLP, recommendation systems, or forecasting
• Leadership experience and ability to mentor high-performing teams

Responsible:

• Lead the end-to-end design, development, and deployment of ML and AI solutions
• Build and operationalise MLOps frameworks for scalable models
• Partner with business stakeholders to deliver measurable outcomes
• Ensure ethical AI practices, explainability, and governance
• Inspire and lead a team of data scientists and ML engineers

Reference Number for this position is GZ60850 which is a permanent position based in Melrose Arch offering a cost to company salary of R1.7m per annum negotiable on experience and ability. Contact Garth on or call him on to discuss this and other opportunities.

Are you ready for a change of scenery? The E-Merge IT recruitment is a specialist niche recruitment agency. We offer our candidates options so that we can successfully place the right developers with the right companies in the right roles. Check out the E-Merge website for more great positions.

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Division: Investment Management

Reference No: 5930

Location:

Centurion, Gauteng, ZA

Employment Type: Permanent

Disability (EE targeted role): No

T.A.S.K Grade: 14

Job Posting Salary: R

Job Posting End Date: 12 Sep 2025

The Road Accident Fund's mission is to provide appropriate cover to all road users within the borders of South Africa; to rehabilitate and compensate persons injured as a result of motor vehicle accidents in a timely and caring manner; and to actively promote safe use of our roads.
Purpose of the Job:
Reporting to Manager: Actuarial Predictive Analytics and Modeling, the responsible for the coordination, preparation and performance of actuarial analysis as required by the RAF.

Key Performance Areas
Actuarial Analysis

• Guide the annual development of the Revenue Requirement Model (RRM) with various funding and/or operational scenarios which will be the basis of discussion with National Treasury regarding the funding requirements and for inclusion in the Strategic Plan and Annual Performance Plan.
• Guide the valuation of assumptions performed by Actuaries and that the statutory actuary performs quarterly valuation on all claims.
• Guide the performing of an independent valuation on outstanding claims also on a monthly and quarterly basis.
• Develop revenue requirement Models.
• Design and execute test plans for data extracts, data transformation and asset and liability management models.
• Analyse a wide range of interest rate risk analysis.
• Gathers and analyses data used in the development of programs and/or models that evaluate the organization`s asset or liability strategy.
• Develop actuarial analysis "payout" models that will redesign compensation packages.
• Design, implement, review and audit of quantitative models for the calculation of Fund's liabilities and capital requirements.
• Review data visualizations and outputs.

Predictive Analytics and Modelling

• Collect, analyse and interpret large data sets in order to provide insights and data-driven solutions to be used in resolving business challenges.
• Implement and monitor predictive analytics solutions by data scientists to improve fraud monitoring detection models and enhance customer experience.
• Implement scalable, efficient, and automated processes for large scale data analyses and model development, validation, and implementation.
• Implement processes of gaining a business understanding, defining the problem, data cleansing and feature engineering, business modelling and simulation, hypothesis generation and testing, machine learning model training, testing and refinement and finally deployment and monitoring of predicted outcomes within the business processes.

Reporting

• Contribute to the preparation and submission of reports.
• Aid in the development of functional reporting systems, for management, project or performance reporting.
• Report regularly and periodically perform necessary submissions as and when required to provide progress updates and/or inform management decisions.

Stakeholder Management

• Proactive and progressive relationships with key stakeholders.
• Deal with inquiries and requests for information from both internal and external stakeholders.

People Management

• Ensure that good employee relations are maintained.
• Provide ongoing operational support to employees.

Qualifications And Experience

• Bachelor's Degree/ Advanced Diploma in Actuarial Science/ Mathematics/ Investment Management/ Risk Management related qualification.
• Relevant 5 - 7 years' experience in an actuarial data science-related environment of which 2 years must have been on a supervisory level.

NB: "RAF offers Total Employment Cost packages with no additional contributions from the Employer, successful candidates are required to structure their packages in a manner that will suit their needs".
The Road Accident Fund subscribes to the principles of employment equity and preference will be given to People with Disabilities.
Applicants who have not received any correspondence from us within six weeks from the closing date can consider themselves unsuccessful
Security Vetting shall be conducted on all prospective employees
It is the applicants' responsibility to have foreign qualification evaluated by the South African Qualification Authority (SAQA) and to provide proof of such evaluation.

• Define and implement the AI strategy aligned with the bank's objectives.
• Manage and mentor a team of data scientists, ensuring high-quality AI/ML model development.
• Oversee the development and deployment of AI/ML solutions for business problems.
• Collaborate with stakeholders to identify opportunities for AI-driven innovation.
• Monitor AI/ML model performance and ensure alignment with ethical and compliance standards.
• Promote data-driven decision-making across the organization.

• Bachelors or Masters degree in Data Science, Machine Learning, Computer Science, or related field.
• 5+ years of experience in AI/ML model development and deployment.
• Strong leadership and team management skills.
• Proficiency in Python, R, and relevant ML frameworks.
• Experience with cloud-based AI solutions (AWS, Azure, or GCP).