See if I'm a fit Women in Data · Key takeaways
Divya Bokaria and Carolina Cabrera compare the choices available to women in data, what strong hiring looks like and why inclusive teams have to be built deliberately.
What stood out
Senior technical careers need credible individual-contributor and hybrid paths. Women should be able to deepen their expertise, influence decisions and keep developing without being channelled into people management.
Leadership and principal-level work are often defined too narrowly. Strong data organisations value empathy, collaboration and technical understanding across both paths instead of treating them as separate strengths.
Divya looks for people who learn from colleagues, think clearly and care about the product and its context. In analytics, understanding the problem behind a request matters more than being a specialist in one tool.
Tools and missing technical knowledge can often be learned quickly by a capable, curious person. Broadening the criteria creates opportunities for candidates who could excel but have not yet been given the conventional experience.
At the time of the conversation, companies were hiring more carefully, but data had generally not been overbuilt in the same way as some other functions. Foundational analytics, product insight and emerging AI use cases still created demand.
A company’s management team and its representation in technical roles reveal more than general statements about diversity. Candidates can also look for leaders who recognise gaps and are prepared to change them.
A diverse pipeline does not appear by accident. Leaders have to question familiar criteria, search more deliberately and accept the risk of trying a better approach rather than defending an unsatisfactory result because every old rule was followed.
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