Original post: Beyond Technical Skills
The “Women in Data & AI” event, a collaboration between TechWomen, Deloitte and Databricks during Techweek25, brought together three accomplished professionals to share their journeys into data and AI careers. Hosted at Deloitte’s Auckland office, the panel featured Caroline Schischka from Deloitte, Hanieh Khalesi from Microsoft, and Angela Zhao from Genesis Energy—each offering unique perspectives on breaking into and thriving in a rapidly evolving field.
Diverse Pathways into Data Careers
A striking theme across all three panellists was that none followed a traditional technical path into data and AI. Their stories challenged the common misconception that you need a computer science degree or deep technical background to succeed in the field.
Caroline Schischka, an Associate Director in Deloitte’s AI and Data team, shared her unconventional journey that began with a Master’s in Psychology. “At school I really didn’t know what I wanted to be when I grew up. I still actually don’t know what I want to be when I grow up,” she admitted candidly. After completing her psychology studies, she discovered her true passion when using data to answer client questions in HR and recruitment.
“What I noticed, what I really gravitated towards, was data and trying to answer client questions through data,” Schischka explained. This interest eventually led to an opportunity to establish a data function at her previous consultancy, launching her career in the field.
Hanieh Khalesi, Enterprise Sales Executive for Azure Data & AI across public sector and education organisations at Microsoft, shared a similar non-linear path. With an engineering background, she has been in tech for about fifteen years but hasn’t always focused on data. Her journey included working with control systems and electronic security before witnessing the transformative power of data analytics.
“I was lucky enough to be part of the transformation journey,” Khalesi reflected. “I saw the shift to leveraging the data we were getting from the integrated building systems and running dashboards and getting insight from the data, which meant there was a lot more efficiency and it was a game changer.”
Challenging the PhD Myth
One of the most persistent misconceptions the panel addressed was the belief that advanced degrees are necessary for data careers. Angela Zhao from Genesis Energy, who transitioned into data management six years ago, tackled this head-on.
“Maybe you heard of this one. You have to be a PhD to enter data. False. Obviously,” Zhao stated emphatically. While expressing respect for those with doctoral qualifications, she emphasised that many technical roles today require human skills that can’t be taught in academic settings.
“A lot of the technical jobs today actually require a lot of human skills,” she explained. “AI has made technical jobs and tasks much easier to learn. You can actually learn the technical side of things.”
Schischka reinforced this point, sharing how she initially felt imposter syndrome during her career transition. “I almost had this imposter syndrome… I was like, oh my gosh, I need to do another masters. So I ended up doing a master of analytics,” she recalled. “But what I found is the technical skills I learnt in that actually didn’t really help me.”
The Human Skills Advantage
When asked about essential skills for those entering data and AI fields today, all three panellists emphasised capabilities that transcend technical knowledge:
- Continuous learning – Zhao highlighted this as “the mother of all skills,” stressing the importance of learning quickly and continuously without seeing it as a burden.
- Critical thinking about AI outputs – As AI tools become more accessible, the ability to evaluate and question their results becomes increasingly valuable.
- Communication and collaboration – The ability to translate complex technical concepts for different audiences emerged as a crucial skill across all three speakers’ experiences.
- Storytelling – Khalesi emphasised how the ability to interpret data and explain what it means to stakeholders at all levels has become essential in her role.
- Curiosity – All panellists agreed that inquisitiveness and a desire to keep learning drive success in the field.
“AI is not going to take your job, someone with AI skills will.” — Hanieh Khalesi, Enterprise Sales Executive for Azure Data & AI, Microsoft
Creating Your Own Opportunities
A powerful message for attendees came from Zhao, who encouraged women to proactively create their own opportunities rather than waiting for them to appear.
“Create opportunities,” she advised. “I did some hard work in terms of certification and prep and networking and talking to others and getting sponsors and mentors, all of that helped. But the one thing that helped me was that I created an opportunity for myself.”
She noted that this approach—asking directly for what you want—wasn’t something she would have done earlier in her career as a younger woman, but it proved transformative in her transition to data.
Building Community and Confidence
The panel emphasised how crucial supportive communities are for women in tech fields. Khalesi shared that mentors and encouragement from others helped her overcome self-doubt.
“Often we might think, oh, probably don’t have the skills or probably can’t do it. So I think my advice is to have mentors and have people in your circle that really empower you and encourage you to do your best,” she advised.
Schischka added that there’s no single correct path, pointing to the diverse journeys represented on the panel: “There’s no right or wrong way as well, and pre-tell from the stories told today—we’re not from data, here we are.”
The Future of Data and AI
When asked to describe in one word what excites them most about working in data and AI, the panellists offered revealing perspectives:
- Zhao: “Prosperity” – Referencing Sam Altman’s vision of artificial super intelligence creating “a super era for prosperity and abundance for all human race” within the next 6-9 years.
- Khalesi: “Empowerment” – Highlighting how AI and data tools enable people to achieve more than previously possible.
- Schischka: “Fun” – Emphasising the constantly evolving nature of the field and the enjoyment of never knowing what will happen next.
What’s Next for Women in Data
The session concluded with networking, allowing attendees to connect with the panellists and each other—reinforcing the event’s focus on community building. Yvonne from TechWomen also highlighted their ShadowTech programme, which connects high school girls with tech businesses for a day, encouraging the next generation of women in technology.
Check out the Techweek25 programme for more great events.
For those interested in getting involved with TechWomen or learning more about future events, visit techwomen.nz.
