Interview With Emma Okere, Data Scientist.

Emma Okere, Data Scientist.

Q. Where did you start your actuarial career and start pursuing data science?
During my final year in high-school, as we were applying for university courses, my father advised me to consider a career in the Actuarial profession. To be honest, I didn’t know a whole lot about Actuarial Science, other than you needed to be good with numbers and that it had the most promising job prospects. From there, I started my journey by pursuing Bachelor of Science in Actuarial Science at university.

“At its core, Data Science is about extracting in-sights” .

Upon graduation, I joined the KenBright team as an Actuarial Intern. At Ken-bright, my first task was in Data Science. My boss asked me to Web Scrap data from a website using Python. At this point, I was completely clueless about programming and it freaked me out! He also handed me a book “Introduction to Data Science” from London Business School on the same day. It was after I read that book that I developed so much interest and passion in Data Science.

Q. What is data science according to you?
There is so much debate about what Data Science is, and what it isn’t. Does it only deal with Big Data? What is Big Data? What makes it different from statistics? Big Data and analytics are topics embedded firmly in our business dialogue. Data is everywhere! The amount of data we’re now generating is astonishing, in fact today’s digital universe has more than 2.7 Zeta bytes of data and this is projected to grow to 180 zeta bytes by 2025. At its core, Data Science is about extracting insights and information from data in various forms, either structured or unstructured and using these findings to generate business value. It’s about surfacing hidden insights that enable companies to make smarter data driven business decisions, thus reducing the variability of outcomes while improving financial and product performance. Data is such an asset to future strategists, thanks to the power of predictive analytics. It all starts with data exploration. When presented with a massive amount of Data, a Data Scientist becomes a detective by investigating leads and trying to understand patterns or characteristics within the data. Along with interpreting large sets of data, a Data Scientist may also be tasked with creating visualization models that illustrate the business value of the insights derived from the data. Data Scientists possess a combination of statistical, communication, creative analytics, data mining as well as machine learning skills. Machine Learning is a branch of Artificial Intelligence that helps to automate data-processing.
It integrates advanced algorithms that learn on their own and can process huge amounts of data in a fraction of the time it would take an experienced human. This will enable an organization to increase efficiency, reduce costs as well as recognize new market opportunities.

Q. What made you decide to be a data scientist?

I was never used to making decisions based on gut feeling, perhaps because the gut may say one thing today, and something completely different the following day. On the other hand , data “is what it is’, unless it is tampered with. Data Science is also a lucrative career that has a great future. A couple of forces are playing a part in making this field better everyday. The number of sensors( phones, satellites etc) is in-creasing, there is decreased cost of storing data and increased accessibility due to cloud networks, computing power is also increasing with the discovery of quantum computers, insight-extraction algorithms such as Machine learning and deep learning techniques are get-ting more sophisticated. All these forces make me believe that Data Science is here to stay!

Q. What do you think is the most valuable skill of a Data Scientist?

There is something special about being able to identify patters and predict scenarios from amorphous sets of data. This requires the right combination of the right skills such as creative analytics, data visualization, predictive modelling and communication. According to me, I think that all these skills are equally important.

Q. What do you enjoy the most about being a data scientist?

Training in Data Science has made me a Data-Driven Decision Maker, this has helped me make better decisions in other spheres of my life as well.

Q . Any Advice for actuarial students all over Kenya?

I highly recommend that actuarial students start pursuing online courses that will equip them with the right technical skills (e.g. Advanced Excel) required in the industry. For those interested in Data Science, Python and R are the best programming languages to learn as they are both free and have a large community of users. I also advise them to participate in the Actuarial Students Society of Kenya (ASSK) events as it is your connection to students who have passed exams and gives you a chance to meet professionals.

Q. Looking back what would have done differently?

I would have believed in myself more.

Q. What have been the influences that shaped your career decisions?

My father influenced my decision to en-roll for an Actuarial Science degree in University based on my good performance in Mathematics. Later on, my boss, Mr. Ezekiel Macharia FIA, became my biggest influence, providing both mentorship and guidance as I joined the Data Science field.