Technology is changing how South Africans work, communicate, analyse information and solve problems. Yet the people building and shaping that technology do not always reflect the diversity of the society using it.
For women in tech South Africa, representation remains an important issue. Women are entering fields such as data science, artificial intelligence, analytics and digital innovation, but significant gaps remain across the wider STEM workforce.
There are also encouraging signs.
Internal Regenesys enrolment data shared for this article indicates that approximately two-thirds of students studying the Postgraduate Diploma in Data Science (PDDS) are women. While this figure relates specifically to Regenesys rather than the South African technology industry as a whole, it suggests strong female interest in developing advanced data and technology skills.
For women who want to strengthen their technical capabilities, the Regenesys Postgraduate Diploma in Data Science provides structured postgraduate study in areas including Python, statistics, data storytelling, machine learning and deep learning.
TABLE OF CONTENTS
Women in Tech South Africa: What Do the Numbers Tell Us?
The broader statistics show both progress and continued underrepresentation.
| Indicator | Statistic | What It Suggests |
|---|---|---|
| Women in South Africa’s STEM workforce | Less than 30% | Women remain underrepresented in STEM employment |
| Female representation among employed tertiary-qualified workers in physical/mathematical and engineering fields | 29.6% in Q2 2024 | Up from 22.2% in Q2 2014 |
| Regenesys PDDS students who are women | Approximately two-thirds | Strong female participation in this specific postgraduate data science programme |
South Africa’s Department of Science, Technology and Innovation reported in 2025 that women represented less than 30% of the STEM workforce, compared with 47% in non-STEM sectors. (gov.za)
There has nevertheless been measurable progress. Statistics South Africa reported that the proportion of employed women with tertiary qualifications working in physical/mathematical and engineering fields increased from 22.2% in Q2 2014 to 29.6% in Q2 2024. (statssa.gov.za)
The Regenesys PDDS figure is therefore particularly interesting. While it cannot be compared directly with national workforce statistics, having women account for roughly two out of every three students in the programme points to a potentially stronger pipeline of women developing advanced data skills.
Why Does Female Representation in Technology Matter?
Representation is not simply about reaching a numerical target.
Technology increasingly influences:
- Recruitment;
- Banking and finance;
- Healthcare;
- Education;
- Customer experiences;
- Government services;
- Business decisions; and
- Artificial intelligence systems.
The people who design, analyse and implement these systems influence the assumptions and perspectives built into them.
Greater participation by women can broaden the range of experiences represented in technology teams and create more opportunities for women to participate in high-growth digital fields.
It can also create visible examples for younger women considering technology careers.
Why Are More Women Moving Into Data Science?
Data science sits at the intersection of technology, mathematics, statistics and business decision-making.
That makes it relevant across many industries rather than only traditional technology companies.
A data professional may work in:
- Banking;
- Retail;
- Healthcare;
- Telecommunications;
- Government;
- Insurance;
- Consulting;
- Manufacturing;
- Marketing; or
- Research.
This versatility may be one reason women in data science are becoming an increasingly important part of conversations about the future technology workforce.
Data science can also appeal to people who enjoy using information to answer practical questions.
For example:
Which customers are most likely to leave?
What patterns indicate financial risk?
How can a company forecast demand?
Which factors influence patient outcomes?
How can organisations use large datasets more effectively?
These problems require more than coding. They involve analytical thinking, communication and the ability to connect technical findings with real-world decisions.
Why Is the Regenesys PDDS Female Enrolment Statistic Significant?
According to internal Regenesys enrolment information supplied for this article, approximately two-thirds of students in the Postgraduate Diploma in Data Science are women.
In simple terms:
About 2 out of every 3 PDDS students are female.
That is notable when placed alongside the broader South African STEM workforce, where women remain underrepresented.
However, the figures measure different things and should not be treated as direct equivalents.
The national figure describes women’s representation across the STEM workforce.
The Regenesys figure describes the gender composition of students enrolled in one postgraduate programme.
What the PDDS figure can indicate is strong female participation in advanced data science education within the Regenesys student population.
Education alone will not eliminate the wider technology gender gap, but participation in postgraduate training can strengthen the pipeline of women with advanced technical capabilities.
What Is Driving Women Towards Technology Careers?
There is no single reason women choose technology.
Several factors may contribute.
Technology Roles Exist Across Industries
A person does not necessarily need to work for a software company to build a technology career.
Banks employ data scientists. Retailers use analytics. Healthcare organisations use data. Governments require digital systems. Marketing teams use machine learning and predictive analytics.
This creates multiple entry points into technology.
Digital Skills Are Becoming More Transferable
Data analysis, AI and technology skills increasingly complement knowledge from areas such as:
- Finance;
- Marketing;
- Engineering;
- Healthcare;
- Operations;
- Economics; and
- Business management.
A professional can therefore develop technical expertise without necessarily abandoning their existing industry knowledge.
Flexible Learning Can Expand Access
Online postgraduate study can give working professionals greater flexibility to develop technical capabilities alongside employment and other responsibilities.
The Regenesys PDDS, for example, is currently offered online over one year. (regenesys.net)
Visible Women in Tech Can Influence the Pipeline
Representation can become self-reinforcing.
When students see women working as data scientists, analysts, AI professionals, technology leaders and researchers, technology careers can feel more achievable.
Mentorship and professional networks can further strengthen that effect.
Women in Artificial Intelligence: Why Representation Matters
Artificial intelligence is one of the fastest-changing areas of modern technology.
AI systems increasingly influence how organisations:
- Analyse information;
- Automate processes;
- Personalise services;
- Detect risks;
- Recruit employees;
- Communicate with customers; and
- Make predictions.
This makes the participation of women in artificial intelligence particularly important.
AI models are built using data, decisions and assumptions created by people. Diverse teams can help identify questions, risks and perspectives that more homogeneous teams may overlook.
Women therefore need opportunities not only to use AI tools, but also to participate in:
- Data preparation;
- Model development;
- Machine learning;
- AI governance;
- Data ethics;
- Product development; and
- Technology leadership.
Regenesys has also explored this wider issue through its discussion of women in leadership, AI, business and inclusive growth, highlighting why access to technology and decision-making matters as AI reshapes organisations.
What Skills Do Women Need for Data Science?
There is no separate technical skill set for women.
Anyone pursuing data science needs to develop the competencies required by the field.
These commonly include:
Python
Python is widely used for data processing, statistical analysis and machine learning.
Statistics
Statistics helps data professionals understand patterns, relationships, uncertainty and the limitations of conclusions drawn from data.
Data Visualisation
Data professionals must be able to communicate findings clearly rather than simply produce calculations.
Tools such as Power BI can help transform datasets into visual information that decision-makers can understand.
Machine Learning
Machine learning allows systems to identify patterns and make predictions based on data.
Deep Learning
Deep learning uses artificial neural networks and is applied in areas such as image recognition, language processing and advanced predictive modelling.
Business Problem-Solving
Technical skills become more valuable when professionals can connect analysis with an actual organisational problem.
What Can Women Study to Enter Data Science?
There is no single pathway into data science.
Some professionals begin with degrees in technology, mathematics, engineering, statistics or computer science.
Others develop data capabilities after gaining experience in adjacent fields.
For graduates who already meet the relevant admission requirements, a postgraduate diploma in data science can offer a structured pathway towards advanced study.
The Regenesys Postgraduate Diploma in Data Science is currently:
- NQF Level 8;
- 135 credits;
- One year in duration;
- Online; and
- Registered under SAQA ID 122148.
Its curriculum includes:
- Data Science with Python;
- Data Storytelling using Power BI;
- Statistics for Data Science;
- The Data Ecosystem;
- Deep Learning with Artificial Neural Networks;
- Predictive Modelling with Machine Learning; and
- Project-based learning.
Students wanting a broader overview can also read Regenesys Insights’ guide to PGDip Data Science in South Africa.
What Careers Can Women Pursue in Data Science?
Data science qualifications can support the development of skills relevant to several roles.
Depending on education, experience and employer requirements, these may include:
- Data Scientist;
- Data Engineer;
- Business Analyst;
- Quantitative Researcher;
- Risk Analyst;
- Research Scientist;
- Data Analyst;
- Business Intelligence professional; and
- Analytics Consultant.
A qualification does not guarantee employment in any specific role.
Employers may also consider work experience, project portfolios, technical competence, industry knowledge and the ability to communicate analytical findings.
What Challenges Still Affect Women in Tech South Africa?
Growing participation does not mean all barriers have disappeared.
South Africa’s government has identified challenges including access to:
- Funding;
- Mentorship;
- Digital technologies;
- Entrepreneurial support; and
- Opportunities within STEM and innovation.
Women can also encounter broader challenges such as workplace culture, limited representation in senior positions and unequal access to professional networks.
The technology pipeline therefore cannot be strengthened through education alone.
Progress requires attention to what happens before, during and after women enter technology careers.
How Can More Women Enter STEM and Technology Careers?
Improving the participation of women in STEM South Africa requires action at several stages.
Start Exposure Earlier
Girls need opportunities to engage with mathematics, science, coding and technology before making tertiary-study decisions.
Make Career Pathways Visible
Many people hear the term “technology career” and immediately think of software development.
Greater awareness of careers in data, analytics, cybersecurity, AI, cloud computing and digital product management can broaden perceptions.
Strengthen Mentorship
Mentors can help younger professionals understand career pathways, workplace expectations and opportunities.
Create Inclusive Workplaces
Recruitment alone is not enough.
Organisations also need environments in which women can develop, contribute and progress into leadership.
Support Continued Learning
Technology changes quickly.
Short courses, postgraduate study, professional certifications and workplace training can help professionals continue developing their capabilities.
What Does the Rise of Women in PDDS Tell Us?
The approximately two-thirds female representation within Regenesys’ PDDS programme should not be interpreted as evidence that South Africa has solved the gender gap in technology.
National data clearly shows otherwise.
What it does provide is a positive signal.
It shows that, within this particular postgraduate data science programme, women are not a small minority.
They are the majority.
That can matter for the future pipeline.
If more women build capabilities in statistics, Python, machine learning, AI and data interpretation, more women may be positioned to participate in technology-driven industries and decision-making.
The next challenge is ensuring that education translates into meaningful opportunities to enter, remain and progress in the technology workforce.
Conclusion
The story of women in tech South Africa is one of both progress and unfinished work.
Women remain underrepresented across the country’s STEM workforce, yet participation is growing in important areas.
Statistics South Africa has recorded increasing female representation among tertiary-qualified workers in physical/mathematical and engineering fields, while government continues to highlight the need for stronger access to technology, mentorship and innovation opportunities.
At Regenesys, the fact that approximately two-thirds of PDDS students are women offers another encouraging signal: women are actively choosing advanced data science education.
Data science and AI will continue influencing how organisations make decisions and solve problems.
Ensuring that women have the skills and opportunities to participate in these fields will be important not only for gender representation, but for the diversity of people shaping South Africa’s digital future.
Frequently Asked Questions
Are more women entering technology careers in South Africa?
There are signs of progress, although women remain underrepresented in many STEM fields. Statistics South Africa reported that female representation among employed tertiary-qualified workers in physical/mathematical and engineering fields increased from 22.2% in Q2 2014 to 29.6% in Q2 2024.
What percentage of South Africa’s STEM workforce is female?
South Africa’s Department of Science, Technology and Innovation stated in 2025 that women made up less than 30% of the STEM workforce. This indicates that a substantial gender gap remains despite increasing participation
Are many women studying data science at Regenesys?
Internal Regenesys enrolment information supplied for this article indicates that approximately two-thirds of students enrolled in the Postgraduate Diploma in Data Science are women. The figure refers to Regenesys PDDS participation and should not be interpreted as a national data science statistic.
Is data science a good career option for women?
Data science is open to anyone with the necessary interest and capabilities. It combines analytical thinking, statistics, programming and business problem-solving and can lead to opportunities across industries such as banking, retail, healthcare, government and consulting.
What skills are needed for a career in data science?
Common skills include Python, statistics, data cleaning, data visualisation, machine learning, critical thinking and communication. Professionals also need to understand how analytical methods can be applied to practical business or organisational problems.
Why are women important in artificial intelligence?
AI systems can influence decisions affecting customers, employees and society. Greater diversity among the people developing and governing AI can introduce a wider range of perspectives when identifying risks, testing assumptions and designing solutions.
What can women study to enter the technology industry?
Possible pathways include qualifications in data science, computer science, information technology, engineering, statistics and related disciplines. Postgraduate qualifications and professional training can also help graduates develop more specialised technology skills.
What is the Regenesys Postgraduate Diploma in Data Science?
It is a one-year, online NQF Level 8 qualification worth 135 credits. The programme includes subjects such as Python, statistics, data storytelling, machine learning and deep learning.
What careers can a Postgraduate Diploma in Data Science support?
Depending on experience and employer requirements, the skills developed may support roles such as Data Scientist, Data Engineer, Business Analyst, Risk Analyst, Quantitative Researcher and other analytics-related positions.
How can South Africa encourage more women into technology?
South Africa can strengthen participation by expanding STEM exposure, improving digital skills development, providing mentorship, creating inclusive workplaces, supporting professional networks and ensuring women have opportunities to progress into technical and leadership positions.
