Welcome to the first feature of ‘HerStory’. ‘HerStory’ is a celebration of remarkable women in the tech scene of Maldives.

From pioneering figures to rising talents, ‘HerStory’ will put a bright spotlight on the extraordinary women who are breaking barriers and shattering glass ceilings.

With this series, we aim to empower and inspire the next generation of female leaders by sharing these powerful narratives of passion, resilience, determination, and success.

And so, our first feature takes a look at one of the most prominent members of the Tradenet team. She is also widely known for her work in several NGOs, as well as for her expertise in the field of data science.

We had a chat with Data Scientist Mihna Zahir. This is her story.

1. Can you introduce yourself and tell us a bit about what you do?

My name is Mihna Zahir and I work as a Data Scientist at Tradenet Maldives. In addition to that, I also work as a freelance data consultant with a background in data science, machine learning, and technology management.

Currently, my main responsibilities include collecting, extracting, transforming, loading and analysing diverse datasets from our partner agencies. In the initial phase, I do a data study of each agency and provide them with recommendations to structure and assist them to harmonise their data for analytics. After that I facilitate the formulation of well informed decisions by leveraging their data.

Given the prevalent absence of standardised data structure and storage methodologies across numerous government entities, as well as not having the proper policies in place to exchange data from one agency to another agency are some of the challenges I face while embarking on this journey.

I am devoted to giving back through volunteering, depending on my availability and workload, I dedicate my free time and skills to initiatives like Women in Tech Maldives and I also collaborate with two international NGOs at the moment. During these engagements, I volunteer to train people in analysing and visualising data using various analytical tools as well as conduct training sessions to increase data and digital literacy within the communities.

2. What drew your interest to the data science field?

My parents played a pivotal role in nurturing and supporting me. While my peers aspired to embark on other career paths like medicine and law, my parents encouraged me to pursue my own passions without imposing any predefined career paths. Their endless support, love, and understanding allowed me to chase my dreams and become who I am today. I am very grateful to be blessed with such wonderful parents and thank them for everything.

Growing up, I was a curious kid. I always asked a lot of questions and wanted to learn new things. Along the way, I developed a fondness for numbers and Mathematics. So, I guess that’s where my interest in the data science field came from.

I am a very family-oriented person, hence I always wanted to have a job where I can spend more time with family while pursuing a career and a job that allowed me to work from home if needed. I always wanted to work in an area which had the power to make a difference.

Growing up, I realised that technology would make a huge difference in our lives and it is always changing, which means the learning process never ends and since I loved to learn and research new things, this felt like the perfect field to embark on.

3. What was it like getting established in the field?

I don’t believe I am established yet, I believe this is a journey, and that I learn along the way. My journey in the field of data science did not start in the Maldives.

Despite returning home after my studies, due to the lack of job opportunities in the area, I couldn’t secure a job in the field here so I accepted a job offer abroad where I joined a vibrant tech startup which consisted of a diverse team.

Over there, under the guidance of my amazing mentors, I navigated through various data projects, finetuning my skills and gaining invaluable experience in leveraging data for strategic decision-making across diverse sectors including agriculture, banking, healthcare, sports and the automotive industry. This helped me understand data across various industries and its application in machine learning.

Additionally, I also took up consultancy projects for EU and various UN agencies as a data science specialist and volunteered to empower women through data analysis training initiatives.

After a few years, I secured a job here in Male’ and returned home to Maldives to be closer to my family and serve this country in the field. I learnt many new things and learnt to adapt myself to working here in Maldives.

After moving back to Maldives, I realised that Maldives is still in the early stages of leveraging data for decision-making and there is low data literacy within the country. Lots of people’s personal data is out there and we have no laws and regulations that ensure data security and as a country, we lack policies in place for data governance and data security.

I came to understand that in most places the data storage practices lacked the sophistication required for running machine learning models, necessitating a foundational overhaul to ensure accuracy in predictive analytics. I also came to realise that while the demand for data scientists was limited, there is a pressing need for data architects and data engineers.

Another challenge was demystifying the role of a data scientist. In this field, it is crucial to acknowledge that no individual can be an expert in every facet of data science, which is an expansive field with lots of different roles and responsibilities.

In addition to these challenges, I encountered significant challenges in my personal life. Despite life’s curveballs at a young age, I persevered through adversity shaping the journey that led me to where I am today. Without those challenges, I don’t think I would have reached here.

4. How does a day in your life as a data scientist look like these days?

These days, till afternoon my day is mostly filled with meetings, mostly because we are still in the early stages of our data journey here at Tradenet and there is a lot of planning needed for all the agencies we have onboarded so far.

Each day usually commences with discussions and consultations with various agencies and stakeholders. I sit with them to understand their currently available data, come up with a plan to study their data repositories and how they can leverage data for analysis and decision-making. In instances where data remains in hard copy formats, our team facilitates the digitization process.

Following the initial assessment, we formalise our collaboration through the signing of NDA’s between the agency and Tradenet, paving the way for cleaning and harmonising the data where needed before data migration onto our system so that we can facilitate their analysis and data visualisation process effectively and eventually utilise this data for machine learning in future.

Each dataset is unique and requires a tailored approach as all our agencies have a different background.

While our data journey here at Tradenet is just beginning and we do have a long way to go, the prospects ahead are immensely promising. I am grateful to be part of an exceptional and supportive team.

5. What advice would you give to young girls who want to establish themselves in data science?

The tech industry presents a vibrant and diverse landscape, offering ample opportunities for women to actively shape the future.

With digitisation and demographic shifts underway, the coming years will witness a surge in demand for highly skilled professionals, leading to innovative job prospects in these fields. It is imperative that these roles are filled by women to foster gender equality in STEM careers.

In the digital economy, data is the new oil and we need more people who are proficient in collecting, analysing, applying and interpreting data for actionable insights. And it is significant to involve more women in this process.

There are many job opportunities in the data science domain such as data architects, data engineers, data scientists, data analysts, business intelligence developers, machine learning engineers and artificial intelligence engineers.

I believe that women bring invaluable perspectives and insights to the tables, enriching the field with unique skills and experiences.

As a woman, you will encounter numerous challenges in life. However, do not allow them to deter you from pursuing your dreams. Aim high, dream big and soar to great heights no matter what.