From Data to Empowerment: Insights from the Women In Data conference

From Data to Empowerment: Insights from the Women In Data conference

On 7 March, I had the privilege of being among the 3,000 women and allies in data attending the 'World's Largest Female Data and Tech Event'. Attending the Women in Data Conference for the first time, my initial expectation was to forge new connections within my industry. However, I left with far more than I anticipated, including new communication tools.

The event showcased an array of activities, featuring talks on the main empowerment stage alongside smaller, sign-up sessions. Surrounding these were company stalls covering a vast range of topics, from private companies discussing AI and data structures to organisations focusing on women's health issues. I participated in 13 talks that covered a variety of subjects, including panel interviews on AI in healthcare and motivational speeches. Of these, two were particularly impactful, offering fresh perspectives and insights.

"Unlocking Data: Empowering 25,000 Employees by 2024" with Johanna Hutchinson and Toni Farrell was the first that stood out.

Johanna was recently recognised as the 6th most influential figure in UK Data for 2024 by Data IQ. Currently the Global Chief Data Officer at BAE Systems, her career includes leading data teams and initiating data transformation. In her conversation with Toni, Johanna focused on her significant contributions to public service, developing data and analytical products during the COVID-19 pandemic — a crucial advancement in understanding the disease, from tracking prevalence to devising exit strategies from lockdown.

What resonated with me was Johanna's approach to challenges and opportunity. She recounted accepting the role of Head of Data Analysis for COVID-19, despite not knowing all the job specifics, confident she could leverage her vast experience in a critical government period.

She cited an internal report by Hewlett Packard highlighting a gender disparity in job application confidence: men apply when they meet 60% of the criteria, while women often wait until they meet every requirement. Johanna's discussion inspired me to adopt a bolder career approach, valuing self-confidence and transferable skills to make a meaningful impact.

"Data and AI For Healthcare Transformation" with Dr Helen O'Neill, Elisa Sai, Ming Tang, and Dr Caroline Morton was another highlight. 

With my background in health, I was eager to learn from the panellists about AI adoption in their companies. Ming Tang, NHS Chief Data & Analytics Officer, has been pivotal in revolutionising NHS data interaction, overcoming the challenges of integrating data schemes and creating Machine Learning models that forecast bed numbers and A&E predictions.

Elisa Sai, Vice President of Analytics & AI at Capgemini Invent, shared her diverse career path before specialising in data, conveying how her varied experiences have shaped her values and anchored her goals. Like Ming Tang, Elisa stressed the nascent stages of AI integration in healthcare, the efforts to ensure data balance in AI models, and the significant need for infrastructure to facilitate effective integration.

Dr Caroline Morton, with roles in research and development at the Bennett Institute, combines her expertise in epidemiology and software development to tackle NHS challenges. Her discussion brought to light gender disparity in data-related fields, especially in software development. The imbalance not only narrows the spectrum of female perspectives but also allows women in the sector to ascend rapidly—a situation that, while advantageous, is not without its complications. Dr Morton commended the UK's healthcare data quality but noted a significant skills gap in data infrastructure development, which could delay crucial implementations.

The key insight from the interview is that we're still at an early stage in the integration of AI, focusing heavily on the initial steps of gathering data to nourish our models. The concept of "ground truth" takes centre stage in our efforts at Zeki, demanding considerable time and attention in both planning and collection due to its significant influence on model accuracy. Like many organisations, we understand that the precision of our data directly correlates with our ability to develop more accurate and representative AI models. However, it's clear that data alone doesn't pave the way for AI implementation; the architecture and pipelines that facilitate data transformation are equally crucial. I'm keenly observing this development and am eager to see how various companies integrate AI into their infrastructures, marking a new era of technological advancement.

Attending the "Women in Data" conference was a transformative experience for me as a female data operations analyst. The event showcased the achievements and challenges faced by women in the field, offering valuable insights and inspiration. It also highlighted diverse career paths and opportunities within data science that I don’t get to see in my day to day. Engaging with a community of like-minded professionals fostered a sense of belonging and empowerment. Hearing firsthand about innovative solutions to gender-specific challenges and biases equipped me with strategies to navigate my career, potentially accelerating my professional growth and impact within Zeki.

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