How Irfan Iliyas successfully transitioned his career from Life Sciences to Data Science & AI in 2021

Irfan Iliyas Case Study image

Irfan Iliyas enrolled and leapt into our full-time 3-month Data Science & AI Singapore program last year. He was dedicated to making a complete change in his career, moving away from his background in human disease science and wanting to remain relevant long term. 

Driven by a desire to secure his future, he decided to upskill in the Data Science world.

And in just 3 months, he adopted the most relevant and in-demand skills in the market facilitating a successful job placement with the National Cancer Centre Singapore as a Research Coordinator. 

He now utilises many of the skills learned in the course to contribute and advance development in cancer research. Have a read of his story here, where he also provides his best interview tips for those who dream of a career in data science:

Can you describe your career experience before making the change to data science & AI? (professional background, qualifications, years of experience)

“My background has always been Life Sciences due to my interests in diseases and understanding what’s going on in the human body. I recently graduated with a Bachelor’s Degree in Biomedical Science and intended to pursue a career in the relevant field. In terms of career experience prior to Data Science, I only had an internship and part-time experiences as a Data Entry Clerk at the National Cancer Centre Singapore (NCCS).”

What were your career goals before upskilling to data? How has your outlook changed?

“As a fresh graduate, my career goals were to gain professional working experience in the Biomedical Science industry by working for a few years and subsequently pursue a Masters in a specific area of interest. In terms of my life, I wanted to properly build up on my savings.

At the time, I didn’t have my Degree Certificate yet due to unfortunate delays within the University. So, I was struggling to get a job because most companies required a certificate. In addition, due to the pandemic, it became economically harder for companies to hire new staff.

That was when I remembered reading up about Data Science during my final year of study. It definitely piqued my interest when I read about how Data Science and Artificial Intelligence (AI) are transforming the Science, Medical and Healthcare sectors. I realised that a Data Science/Analytics career is for the long-term future as the field is in strong demand. It made me reevaluate my career goals. I wanted to learn more about it and thought that I should pursue a Data-related career in Singapore’s Healthcare industry instead.”

Why did you choose to join the Full-Time Program in particular? What appealed to you?

“I was attracted to the Data Science and Artificial Intelligence Program by Institute of Data (IOD). As an upskilling course, I felt that the modules would provide the perfect foundation due to their relevance to many job scopes today. In addition, a subsidy is given to all Singaporeans taking on this course, which makes it more affordable as compared to other Institutions with similar courses.

As I wasn’t working, I thought it would be a great opportunity to take up the Full-Time Program due to the large amount of free time I had. Another reason for taking up the Full-Time Program was that the duration of the course was only 3 months, as compared to the Part-Time Program which runs for 6 months. This would mean that I could start working as early as possible.”

What was the most challenging aspect of completing the course and what did you enjoy the most?

“The most challenging aspect of completing the course was understanding the basic concepts of coding. Coding is new to me as I have never learnt it before. I had difficulties understanding why certain things are specifically coded in some ways and not others, how codes are arranged and described in a text, and the errors that I faced. I am fortunate enough to have kind and considerate trainers who remained patient with me and continuously believed in my abilities.

The trainers taught me well, and I couldn’t be more appreciative of them. This leads me to share what I enjoy most about the course. With the guidance of the trainers, I was able to understand coding better. The most enjoyable (and rewarding) part of the course is when I figured out the right codes to solve the tasks. This motivated me to keep going and complete the course.”

You’re now working with National Cancer Centre Singapore as a Research Coordinator – Congratulations! How did you get a job in the industry after completing your training and what guidance would you give someone applying for jobs after upskilling?

“Singapore’s Healthcare industry is increasingly implementing AI into the works for the advancements of medical technologies. Recently, NCCS has opened up a number of job opportunities in relation to Data Science/Analytics. No doubt in my mind that I wanted to return to NCCS. I felt it was a good opportunity to work there again due to my prior experience. In addition, I remained in contact with my former supervisors at NCCS. 

I was fortunate enough to be linked up to an Associate Consultant (AC) who was looking to hire someone with some knowledge in Python and Machine Learning. In the first interview, I shared my experience with the course I took. The AC was impressed by how much the course had provided me, which is relevant to the role he was offering. After 2 interviews, I secured the job.

To those who are applying for jobs after upskilling, I would advise that they should be aware of the industries where Data Science and AI are increasingly or strongly present. These companies are good options for the long-term future and would most likely provide good career progression. 

I would strongly encourage them to apply to companies that are in need of Data Scientists/Analysts or other Data-related roles. If they had prior working experience with a company that is currently implementing Data Science and AI into their works, I would advise new applicants to return to the company, if possible. Their experience would give them the edge over other applicants as they would know the expectations of the company. A good past working relationship and work ethic with the company would also give an added advantage.”

How do you prepare for a data science interview? What are the most important things to remember and discuss with a potential employer?

“For any interview, my preparations would always involve writing down notes prior. One of the most important things to know is the company you are applying to. It is very important to understand the current and future projects of the company, and how they function on a day-to-day basis.

In the case of a Data Science interview, you must know and understand the skills you have gained (You may share the knowledge and skills from the Data Science course). This is important as you would be able to explain how you could make valuable contributions to the company with your skill sets.

It is highly encouraged to prepare questions about the company. This shows that you are keen to know more about them. An important thing to find out is their expectations. This is so that you are aware of their workflow and how you can meet their requirements. Although this is optional, I would advise new applicants to know the work culture of the company. I feel it is important to know the people you would be working with. If you have doubts or are struggling with certain tasks, you would know that there are immediate colleagues you could turn to for help.

Besides questions, you could also share your career goals with the company. It will be good for the company to know, and with a good working relationship, the company may offer future opportunities to help achieve your goals.”

Tell us about your current data science role, what does your day to day involve? What tools or processes do you use?

“I’m currently working as a Research Coordinator (RC) at NCCS. My role involves skills such as those in Python, Natural Language Processing (NLP), Text Classification, SQL and Deep Learning Models. I used these skills to (1) provide assistance in clinical analytics research projects, including processing and analysing datasets, (2) study images, video and clinical text data, and (3) manage databases. Some of the tools or processes I used include Anaconda, Jupyter, Spark NLP and Amazon Web Services (AWS). In addition, I am picking up new skills such as R, and learning to use the new programs such as Label Studio, INCEpTION, Docker, Mirai and VMware.”

What is one thing you know now that you wish you knew before changing careers to data?

“I wish that I had more courage to take up a Data Science course as part-time at an earlier stage of my life. A few years ago, I was already aware that Data is in demand and the Healthcare industry in Singapore is already implementing machine learning and AI into modern medical technologies. However, I chose against pursuing it due to fears that I may struggle in coding. Upon completion of my Bachelor’s course, I applied for various full-time jobs relevant to my field but struggled to receive any offers due to the ongoing pandemic.

I looked through a number of job platforms and saw that there were many Data-related roles available in the Healthcare industry. I felt a bit of regret that I did not pursue Data Science. Having such skills could have improved my chances of getting a job. That made me research various Data Science courses, and I stumbled upon the Data Science and AI program by the Institute of Data (IOD).”

Your Capstone Presentation also achieved top results. How did you prepare for this presentation?

“Given that it is a Capstone Presentation, I felt it would be good to showcase my understanding by using the skills I have picked up from the course to the field I am currently in, i.e. Life Sciences and Healthcare. This way, I can also showcase my Capstone Presentation as part of my portfolio to future employers in my field. I came up with a few ideas and researched appropriate dataset samples I could use. I then shared the ideas with my trainers. After a few good discussions, I decided to go with one.”

How did you find the process of completing your final Capstone project during the course? What did it teach you?

“On the basis of coding, the process was challenging. There were requirements to meet for this Capstone Presentation such as proper cleaning of the data and balancing the data. I faced a lot of coding errors as well. There were a few times when it became frustrating. Despite these complications, I remain determined to resolve them. What I have learnt is that these complications do exist in the real life of the Data industry. Data extracted from a particular source will not appear as a perfect dataset and thus, it must be thoroughly cleaned. There will be times when we do run into errors, which will require brainstorming to troubleshoot them.

On the basis of the presentation, it was important to be wary about the way I presented my slides. I learnt that it is essential that we take control of the eyes of the audience. Adding animations and transitions to the slides are brilliant ways to do so. These ensure that everyone’s eyes are focused on the correct parts of the slides and not drifting elsewhere at any given time. In addition, I needed to consider the various backgrounds of the audience. I am a student with a Biomedical/Life Sciences background and I couldn’t simply assume that everyone would have excellent scientific knowledge. Therefore, it was very important that I explained and used basic scientific concepts and terminologies clearly so that everyone could understand.”

In your opinion, how did the program change your perspective on the importance of soft skills in a data science role?

“The program made me realise that anyone without any prior knowledge of Data Science can actually pick up such soft skills. Data Science may be more challenging for some like myself, but with practice and commitment to learning, these skills can be vital in various industries today. Having these soft skills has already provided me with a platform to handle my day-to-day tasks, and go further. I felt that the course prepared me well, not just having the solid foundation to know how to use common tools and programs, but also adapting, picking up and learning new skills and programs efficiently.”

Do you have any advice for professionals making a career change and entering the field of data science?

“A strong advice I would give to professionals is to have an open mind when they are learning about Data Science, regardless of background, experience or academic achievements. Possessing skills in Data can help professionals stay relevant in the workforce as many companies are gearing towards technology and AI today. 

In addition, Data Science is actually a very big subject. It is important to have an open mind, not just to learn about the current concepts, but also to explore further. You will realise that there are various methods of coding, as well as futuristic tools and programs available.”

Connect with Irfan on LinkedIn.

If you are interested in up-skilling and transitioning your career to the Data Science field in Singapore, schedule a consultation with a Data Industry Career Consultant today.

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