3 Data Analysis jobs in South Africa

Purpose of the Job:

To analyse data systems, create automated systems to retrieve information from database and compile reports. The department will also use data to solve problems, to turn data into information and information into insight that will lead to informed business decisions, and to create detailed specifications that specify data sources, data flows, data transformations, data storage and reporting. The person appointed to this position will report to the Senior Specialist: Data Analysis.

Key Performance Areas:

•Create detailed specifications that specify data sources, data flows, data transformations, data storage and reporting;
•Produce documentation such as source-to-target-maps, data dictionaries and data models;
•Create test cases and scenarios used to ensure quality assurance;
•Interact and collaborate with technical and business stakeholders to identify data sources, find data definitions for master and meta data as well as formulate and implement solutions;
•Promote the use of existing enterprise data standards to enhance data quality, ensure constant compliance and adherence to data governance principles;
•Process live and confidential data according to specified guidelines;
•Evaluate changes and updates to source production systems that could impact reporting and eventually business decisions;
•Interpret data, analyze results and interpret trends enabling continuous improvement in data quality and overall business performance;
•Defines, implements and standardises metrics, reports and dashboards for the business;
•Deliver key metrics, reports and dashboard with interpretation.

Other Key Competencies:

The applicant must demonstrate the following skills and attributes: active listening, critical thinking, analytical thinking, attention to detail, strong financial and numeracy skills, proficiency in using Ms office, excellent communication skills, good interpersonal skills and emotional intelligence. The candidate must have the ability to establish priorities and manage several tasks.

The FSCA is committed to increasing the representation of marginalised groups in line with its transformation strategy. Persons with disabilities are encouraged to apply.

Please note that correspondence and communication will only be conducted with short listed candidates and that the FSCA reserves the right not to appoint if a suitable candidate is not identified.

A degree or B Tech in Information and Communication Technology (ICT) or a related discipline with at least 4 years’ working experience in a field where analysis of data was major, preferably in a financial services sector. Proven experience building logical and physical data models using industry best practices, patterns and frameworks. Demonstrate knowledge of database and data warehouse design. Knowledge of BI methodologies. Practical technical experience using database management tools and reporting tools.

Closing Date: 18 August 2025

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Date Posted: 07/30/2025
Req ID: 44509
Faculty/Division: Faculty of Arts & Science
Department: Munk School of Global Affairs & Public Policy
Campus: St. George (Downtown Toronto)

Description:

Course number and title : PPG2010H-S – Panel Data Methods for Policy Analysis

Course description : The course provides a rigorous introduction to statistical methods for the analysis of panel data with specific application to the major Canadian longitudinal data sets. This course is offered in collaboration with the Toronto Research Data Centre (RDC). The RDC provides secure access to Canada's preeminent panel data sets for public policy analysis as well as variety of other Statistics Canada data. The course will take place within RDC providing students hands-on experience with these important sources of information on public issues. The RDC offers both lecture space and a computer lab for tutorials. While the specific goal of this course is to introduce students to empirical methods for the analysis of longitudinal data, an important by product is their exposure to the RDC data. Instruction includes a combination of lectures and break-out groups. In break-out groups, students will complete series of problem sets that provide an introduction to the RDC panel data sets and practice in their analysis. The statistical methods reviewed will be drawn from a variety of disciplines to promote the inter-disciplinary study of public policy. Certain topics of particular relevance to the RDC panel data (e.g., cluster sampling, bootstrapping) will also be covered. The course is intended for a) MPP students from the Munk School of Global Affair & Public Policy; and b) students from departments, schools and faculties where small numbers preclude a similar course being offered, or that desire instruction in the use of data housed in the Toronto Region Statistics Canada RDC.

Class schedule : Tuesday 1-4pm
*The delivery method for this course is expected to be in-person.Please note that, in keeping with current circumstances, the course delivery method may change as determined by the Faculty or the Department.

Sessional dates of appointment : January 1, 2026 - April 30, 2026

Salary : Sessional Lecturer I - $9,820.70; Sessional Lecturer I, Long Term - $0,510.04; Sessional Lecturer II - 10,510.04; Sessional Lecturer II (Long Term) - 10,760.28; Sessional Lecturer III - 10,760.28; Sessional Lecturers III (Long Term) - 11,030.36
Please note that should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.

Minimum qualifications : Ph.D. with a specialization in statistical measurement and evaluation required. Extensive knowledge and background in statistical/quantitative methods in social sciences methodology required. Experience and knowledge of applying panel data methods in public policy required.

Preferred qualifications : Experience in teaching in a multidisciplinary context is an asset.

Description of duties : Teaching at the graduate level, developing the syllabus, teaching three-hour classes, providing weekly office hours for academic counseling of students, preparing and delivering course material,preparingand delivering assignments and tests, marking student work and submitting grades.

This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement.

It is understood that some announcements of vacancies are tentative, pending final course determinations and enrolment. Should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.

Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12 of the CUPE 3902 Unit 3 collective agreement.

Please note: Undergraduate or graduate students and postdoctoral fellows of the University of Toronto are covered by the CUPE 3902 Unit 1 collective agreement rather than the Unit 3 collective agreement, and should not apply for positions posted under the Unit 3 collective agreement.

Diversity Statement

The University of Toronto embraces Diversity and is building aculture of belonging that increases our capacity to effectivelyaddress and serve the interests of our global community. Westrongly encourage applications from Indigenous Peoples,Black and racialized persons, women, persons withdisabilities, and people of diverse sexual and gender identities.We value applicants who have demonstrated a commitment toequity, diversity and inclusion and recognize that diverseperspectives, experiences, and expertise are essential tostrengthening our academic mission.

As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see .

Accessibility Statement

The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.

The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.

If you require any accommodations at any point during the application and hiring process, please .