Fan Jiang, a prominent figure in data science at Atlassian, has advocated for enhanced early education in data and artificial intelligence (AI) to encourage more women to pursue careers in technology. Her remarks came after being honored with a Data Science award at the 2026 Women Leading Tech Awards, where she highlighted the critical need for youth engagement in these fields.
Recognized for her innovative contributions to the evaluation and launch of AI-powered products, Jiang developed a groundbreaking “LLM-as-a-judge” metric. This tool assesses the quality of AI-generated code against human standards and has been integrated into Atlassian’s AI experimentation process. The methodology has significantly expedited the iteration of developer tools and was later shared at the International Conference on Software Engineering.
Speaking after her award win, Jiang expressed her honor in representing women in a rapidly evolving data science landscape. “I feel like there’s not a lot of women in the data space in tech, and I definitely feel like we should start the generation young,” she asserted in an interview, emphasizing the importance of familiarizing young people with the data science profession, especially against the backdrop of advancing AI technologies.
Jiang’s transition from an actuary to a data scientist has shaped her perspective on accessibility within the field. She noted that the proliferation of AI tools has lowered the barriers to entry, encouraging individuals of all ages to engage with data. “Anyone can start playing around with data. There’s so much data that’s available in the industry,” she remarked, inviting aspiring data professionals to harness the vast resources at their fingertips.
In addition to her technical achievements, Jiang has been instrumental in fostering support networks for women in her company. She established an internal community named “Women in Data Science,” designed to provide mentorship, career guidance, and shared learning opportunities. This initiative has proven beneficial for over 15 women navigating significant career transitions, reinforcing Jiang’s commitment to empowering female talent within the tech industry.
Jiang also expressed pride in the recognition of women’s contributions to technology, particularly in spaces traditionally dominated by men. “It feels amazing to have an event that’s tailored towards women,” she stated, reflecting on the significance of such platforms in showcasing female talent in tech. “It’s amazing to see so many women in this industry, and it’s incredible to work alongside all of these other women in this profession.”
As the tech landscape continues to evolve, Jiang’s call for early education in data and AI underscores a broader initiative to diversify the industry and inspire the next generation of female leaders in technology. Her efforts highlight the crucial intersection of education, mentorship, and innovation in shaping a more inclusive future in data science and AI.
See also
Andrew Ng Advocates for Coding Skills Amid AI Evolution in Tech
AI’s Growing Influence in Higher Education: Balancing Innovation and Critical Thinking
AI in English Language Education: 6 Principles for Ethical Use and Human-Centered Solutions
Ghana’s Ministry of Education Launches AI Curriculum, Training 68,000 Teachers by 2025
57% of Special Educators Use AI for IEPs, Raising Legal and Ethical Concerns
