Being a girl who was always interested in fixing things, it was a natural choice for Monmayuri Ray to opt for a career in engineering. At every step of the way, she often found herself being the only girl in the room. This would frequently lead to her being sidelined from the task at hand. Instead of taking offence, she would utilise such occasions to bring a unique perspective to the table that would force others to take note.
Now working as a Solutions Architect at GitLab, a software development platform, she is happy to use her skills in mathematics and storytelling. In the past, the Sydney-based data scientist has been associated with global companies like Microsoft, eBay, Quantium and Deloitte. In this conversation with Women Icons Network, she talks about entering fields that are perceived to be male dominated traditionally, the current state of gender diversity at the workplace and its future.
Choosing a Career
While growing up in India, Monmayuri remembers being interested in building and fixing things. She was especially drawn to the task of improving wooden boats, to make them faster, more sustainable and cheaper. As she was also fond of technology, the choice of selecting a field to study was simple; she chose to graduate in mechanical engineering. She holds a Bachelor of Applied Mathematics/ Engineering (Mechanical) & Studio Art from Illinois Institute of Technology, Chicago and a Masters of Philosophy (Biomedical Engineering) from Hong Kong Polytechnic University.
When it came down to selecting a career, she always thought it should be something that was people-focused, and one that allows her to combine her love for both mathematics and art. “Tech was just the medium. Going into technology has been a blessing and I am very fortunate to have been able to utilise both my analytical and creative sides to solve real-world problems,” she says.
She adds that what she loves the most about her job is the ability to harness the capability to solve things through the lens of Artificial Intelligence (AI), making tech work for people through innovations. A specialist in AI and machine learning, Monmayuri is passionate about all forms of data storytelling and the operationalisation of human computer interaction.
Challenges and Lessons
Despite growing in a traditionally male-dominated India, she saw the women in the household sail through life on equal footing with the men. Watching her mother make decisive, swift decisions to solve the little problems that got thrown her way while raising five children was inspirational, she recalls.
As an engineering student, she was often the only girl in her team for projects. On one such occasion, she remembers the men immediately sidelining her, assuring they would take care of the heavy lifting. She didn’t protest. Instead, she volunteered to contribute to the aesthetics of the project which led to a positive outcome for the team.
“My approach was to look at that difference as a positive, to consider that my strengths, along with any preconceptions or biases around me can co-exist,” explains Monmayuri. This is the attitude she has continued to have throughout her career as well. It’s about finding ways to complement one another to see through the end common goal, she adds.
Women in STEM
She believes that careers don’t have an assigned gender. She finds the idea of women not being allowed to or capable of having a career in STEM as an archaic one. “In fact, it almost feels that we have gone the other direction, with diversity metrics now being scrutinised with every hire. Whoever is in or approaching a STEM career now should recognise there is every opportunity for equality, and there is a greater likelihood of a supportive journey ahead,” she says.
Despite the cheery note, Monmayuri shares she has faced a few offensive situations at the workplace, too. One time, a male colleague referred to her as an ‘alpha female’. At the time, she didn’t take it as a derogatory description. “However, upon understanding the context further, it was not only an incorrect judgement but also incredibly sexist, she says.
In another instance, she was faced by a superior at work who asked her to disclose sensitive details about activities outside work. All this because she had taken up modeling and ballet dancing as hobbies. She spoke to the HR, affirming her legal rights in the given scenario which led to the manager in question being apprehended.
Gender Bias at Workplace
“Women at the workplaces are often planning careers around outdated policies, especially those that relate to eligibility of maternity leave, prospects of career progress when someone’s taken maternity leaves. Women continue to go through biological transformation as they juggle careers and other aspects of life, and workplace policies that do not support and are contributing to their under-participation or withdrawal from the workforce,” rues Monmayuri. She believes that more work needs to be done around parental leave policies that promote the widespread discrimination of women.
At GitLab, the phrase “Diversity, Inclusion & Belonging” (or DIB) refers to the initiative to create a diverse workforce and an environment where everyone can be their full selves. “The term Belonging refers to when you feel your insights and contributions are valued. It goes back to team members feeling they can bring their full selves to work. It’s not enough to simply include people to have a “seat at the table”, but it’s important to amplify everyone’s voices, remove barriers and appreciate each other for their unique backgrounds,” she explains .
Additionally, a big hindrance in achieving equality stems from our personal biases, she believes. “Equality requires humans to learn to de-bias how we live, learn and work. Fundamental to gender equality is how men and women de-bias how they perceive the other gender,” opines Monmayuri.
She also refers to Daniel Kahneman’s book ‘Thinking, Fast and Slow’ which solidifies the argument that the human brain is biased and decision-making, in turn, is a highly biased process where the mind is controlled to see weighted information. “My request to the next generation of both men and women would be to ‘think fast and slow’ and in that process, de-bias through genuine data points and metrics in order to create a fair and equitable workplace,” she urges.
While the last few months have been very difficult for everyone in the world, she believes that the human race has coped tremendously. “Personally, it has been heartening to see women finding what’s already natural to them to cope. Whether it’s putting their natural multi-tasking skills on overdrive, relying on their maternal instincts to survive or the ability to be creative and continue thriving,” she gushes.
The journey to a more diverse and equitable workplace takes time, and fortunately, we are on our way, she believes. There are plenty of valid discussions about gender diversity but Monmayuri is interested in the acceptance of diversity, which is a larger economic, political, socio-economic question.
“Diversity is about accepting differences and not forcing men or women, engineers, data artists or decision scientists to fit into the same mould. As we advance towards a data-driven future, AI will require not just data and engineering skills but increasingly, there will be a need to emphasise judgment, decision-making and people skills that transcend gender, backgrounds and limiting job titles or career paths,” she says.