Gender Diversity in Data Engineering

Recently I contributed to a study by Women Leaders In Data & AI (WLDA), KPMG, and Revelio Labs on the career outlook for women in data, analytics, and AI. The results were a real eye-opener, even after decades in the field. With only 39% of the workforce in data, analytics and AI being women, and 77% of executives saying Generative AI (GenAI) will have an outsized impact on society, there’s a lot at stake. We need to attract and retain talent from all backgrounds, not just to fill roles, but to make sure the systems we build are fair, inclusive, and reflect the diversity of the world they’re meant to serve. In this article, I highlight key findings from the study and discuss why expanding the talent pipeline is essential for building a more inclusive future in these fields. Big thanks to WLDA, KPMG, and Revelio Labs for the opportunity to contribute to such an impactful initiative! #DiversityInTech #WomenInData #AI #InclusiveFuture https://lnkd.in/g-uDUgKE

𝗧𝗵𝗲 𝗥𝗶𝗽𝗽𝗹𝗲 𝗘𝗳𝗳𝗲𝗰𝘁 𝗼𝗳 𝗪𝗼𝗺𝗲𝗻’𝘀 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝗶𝗻 𝗗𝗮𝘁𝗮 🌊💼 When women lead, workplaces transform. Revelio Labs' latest study reveals a powerful ripple effect created by women Chief Data Officers (CDOs), reshaping culture and boosting diversity across their organisations. Here’s what the data shows: ✨ 𝟯% 𝗥𝗶𝘀𝗲 𝗶𝗻 𝗪𝗼𝗺𝗲𝗻 𝗶𝗻 𝗞𝗲𝘆 𝗥𝗼𝗹𝗲𝘀: Companies with women CDOs report a steady 3% increase in women in experienced roles over four years. In traditionally male-dominated fields, this shift signals that diverse leadership attracts diverse talent and shows aspiring women that real career growth is achievable. 🤝 𝟭𝟱% 𝗠𝗼𝗿𝗲 𝗠𝗲𝗻𝘁𝗼𝗿𝘀𝗵𝗶𝗽: Women-led teams report a 15% higher rate of employees identifying as mentors. This mentorship culture goes beyond career advice—it builds a supportive network that helps retain top talent. For early-career professionals, especially women, this kind of support is essential in feeling valued and empowered to grow within the organisation. 𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗠𝗮𝘁𝘁𝗲𝗿𝘀: Women’s leadership isn’t just about ticking diversity boxes; it’s about creating inclusive, supportive workplaces for long-term success. When leaders prioritise representation and mentorship, they inspire shifts in hiring practices and foster a culture that promotes retention and development at all levels. Read the full report here: https://lnkd.in/e9HzAen7

This is really SCARY. Only 10% of CEOs and top tech leaders in AI companies are women. Even worse? Most of these top leaders are clustered in HR and legal - completely underrepresented in core technical functions like product, engineering, and data science. The study analysed 426 execs across 39 AI platform and application companies. The gender gap in technical leadership is actually jaw-dropping: 👉 Just 22% of leaders in engineering, product, and applied science roles are women. 👉 Only 4 women CEOs and 4 women CTOs in the entire dataset. 4!!! 👉 4 companies had zero women on their executive team. Ew ew EWWWW Let that sink in. We’re developing foundation models and fine-tuning algorithms that will shape the next generations - they'll influence who gets hired, who gets a mortgage, who gets care - and women are barely part of the architectural decisions. This is not just a diversity issue. It’s a SYSTEMS DESIGN FLAW. AI is only as fair as the data it learns from and the humans who shape its architecture. And when most model training sets, prompt engineering, and algorithmic optimisation are led by homogenous teams, we risk encoding bias at the structural level - then calling it "intelligence." We’ve already seen it play out: ❌ Embedding historical discrimination into resume parsers ❌ Emotional recognition tools that penalise neurodivergence ❌ Recommendation systems that reinforce gender stereotypes These aren’t bugs. They’re consequences of building tech without representative leadership. Did these numbers surprise you - or confirm what you’ve suspected? Keen to hear your take in the comments 👇 #AI #WomenInTech #AIethics #FoundationModels #AlgorithmicBias #ResponsibleAI #MachineLearning #LeadershipParity #ivee #Returners #EquityInTech #SystemicBias