Islam Muhammed’s Data Science Journey

1. Please introduce yourself, what you do, and your current role.

I am Islam Muhammed, a data scientist with over three years of experience in the data field, based in Cairo, Egypt. Currently, I am working as a data scientist at Paymob, a global fintech company driving the digital economy across MENAP. My role primarily revolves around developing prediction models for the merchants’ monthly sales as well as CVM (customer value maximisation) solutions.

2. Tell us about your path into data science. What inspired you to pursue a career in the field? Is this what you’ve always wanted to do?

In 2016, I was impressed by a fully automated production line for car assembly at one of the industry giants in Germany, driven by KUKA Robotics, through a YouTube video. Although my background is in mechanical engineering, the video sparked my curiosity, leading me to explore artificial intelligence, computer vision, and automation in general. I know that robotics and manufacturing are a bit different from what I am doing now, but it was the spark that fueled me to discover this world.

My learning path was entirely self-taught, leveraging MOOC courses, until I joined ITI under the umbrella of MCIT (Ministry of Communications and Information Technology, Egypt). Here, I delved deeper into software engineering and machine learning, honing my skills and expanding my horizons while also having the opportunity to engage with industry leaders in Egypt.

3. What are some of the biggest challenges you have faced on your career journey, and how have you overcome them?

There are two main challenges I have faced so far. Firstly, democratising AI within businesses and fostering awareness about its capabilities while emphasising the critical role of data quality in the ML lifecycle.

Secondly, quantifying the impact of data science endeavours on business outcomes, particularly in scenarios requiring cross-functional collaboration, presented its own set of challenges. However, I’ve found that effective communication and fostering a collaborative environment are instrumental in overcoming these obstacles, especially as organisations scale.

4. What advice would you give to those who are just starting in AI and data science? What skills or qualities do you think are most important for success in this field?

One of the most underrated skills in the data field is soft skills or interpersonal skills. You need to present your solutions well, gather the right information from stakeholders, and ask the right questions. Mastering communication is crucial because you’re often dealing with other people’s problems using their data.

Additionally, solidifying your software engineering fundamentals skills is important to ensure a seamless transition from notebooks to production-grade solutions through modular, clean, and well-architected code.

Lastly, stay abreast of the latest technological advancements in AI and keep a keen eye on multimodal approaches and LLMs, as they hold the potential to revolutionise the landscape of AI.