Welcome back to the four-part series featuring the Women@OCTAVE: Chamodi Adikaram, Data Scientist; Dinusha Dissanayake, Data Scientist; Lamana Mulaffer, Senior Data Scientist; Nadeesha Ekanayake, Senior Data Scientist; and Shashini Gregory, Visualisation Analyst. Today, they will share their advice to young girls enthusiastic about Data Science and Engineering and reveal some tips on how to thrive in this field! Here are their stories.
WOMEN@OCTAVE: Our Work Life
Welcome back to the four-part series featuring the Women@OCTAVE: Chamodi Adikaram, Data Scientist; Dinusha Dissanayake…
What words of encouragement do you have for a schoolgirl interested in Data?
Chamodi: First, be it Data Science or any other profession, identify your true passion and follow it without doubt. Only your skills, abilities, and commitment will determine what you can and cannot do. There is much hype over Data Science, AI, and Advanced Analytics in the last few years and the demand for jobs has risen consequentially. There is no need to worry about the job market.
Most students are unaware that Data Science has a broader scope than just Computer Science. This is an industry by itself with applicability in any area you can think of. I know Data Scientists with backgrounds in physics, chemistry, statistics, space engineering, sociology, and even medicine. This is an industry with more potential than we have discovered so far.
This is a scientific industry that keeps advancing every day. Be willing to learn throughout your career. A curious and investigative mind makes a good scientist. Unlike the stereotypical scientist with test tubes and chemicals in hand, you will be experimenting with data and numbers.
Dinusha: Most people have the misconception that there is a time limit in pursuing your passion. It is never too late to begin your journey in data if you have an interest.
Lamana: Artificial Intelligence (AI) is fast paced, exciting field that touches almost all industries. If you have an interest in a specific topic — sports, for example — you can find ways to apply AI to it. Keep abreast of AI news; the more you discover the impact it has had on the world the more you want to become a part of it. You will find examples of people from different backgrounds — computer science, business, arts — moving into this field, which goes to show that anyone from any age can learn and grow within this space.
Nadeesha: You will be applying the fundamentals of mathematics, statistics, and logical thinking you learnt at school in the Data Science domain. Improve your ability of applying the scientific method with a problem statement, a hypothesis, data collection, data analysis, a conclusion, and solution implementation. It is simple as that!
What advice can you give a female graduate or a junior professional looking to establish themselves in the data space?
Chamodi: Data Science is a relatively young industry, and it still can be a gender diluted industry. As surprising as it may sound, studies show that some female traits correspond to the qualities that make a Data Scientist successful. Therefore, we need more women Data Scientists in the industry. Many companies like John Keells are moving towards increasing gender parity by creating diverse work environments. Make use of these opportunities to establish yourself in this space.
While the Internet is a great resource when starting out in this space, I advise you to bring your own unique strengths to the table. Data Science has professionals from diverse backgrounds. The intersection of these professionals may consist of basic skills such as Mathematics and Programming, but it is your specialization that makes you stand out. It is important to identify the skills, expertise, or even interests that make you unique.
You may be unaware that there are many roles emerging within the Data Science space in addition to a Data Scientist. These include roles such as Analytics Delivery Specialists, Visual Analysts, Data Engineers, Machine Learning Engineers, and Business Analysts. If you are more interested in the Advanced Analytics space and feel like you lack the skillset expected from a Data Scientist, there are many equally interesting avenues that you could branch out into.
Lamana: Become well-informed about AI culture. Familiarize yourself with the global AI field, and you will see that expertise in certain fields has been geographically stimulated. This will help you gain a sense of where AI is heading in the future. Follow popular AI blogs, documentaries, pod casts, and so on. Keep AI news always in your periphery as it is an ever evolving, exciting, and fast paced space. But remember to pace yourself — there’s so much to learn. Keeping realistic goals and you will build a lot of experience. For example, every 3 months, learn a new algorithm and apply it in a project.
If you are on the lookout for a job, your portfolio is key. Make sure it catalogues previous work experience. Do include your personal projects and make sure they are published on a public platform. This is something entirely within your control. The next step is to know who’s who in the AI industry from large conglomerates to start-ups that do projetcs that interests you.
Nadeesha: This is a career with continuous learning and expanding opportunities. You can transition smoothly across a variety of industries such as telecommunication, healthcare, retail, banking, and hotels. It is a comparatively prestigious field for you to achieve exponential growth, economic stability, and financial independency as a woman.
Join us next week for the final instalment in this four-part series, where the Women@OCTAVE take an insightful look at the future of women in Data Science. Tune in to find out the trailblazing women who inspired them!