Meet Florence, Junior Data Scientist
A little bit about me
I am Florence Cesa, a Junior Data Scientist at Haleon based in London, UK.
What did I want to be when I grew up?
My earliest memory of what I wanted to be was a doctor, more specifically, a surgeon. That was, until I learned that I couldn’t handle the sight of blood well, nor the thought of stitching wounds and sticking needles in people.
After learning more about the different sciences, I decided that I wanted to be a scientist, specifically, a chemist. I enjoyed laboratory work and learning about the various analytical techniques in chemistry. I dreamed of working in a lab and little did I know that in my future this dream would come true by working in a different type of lab (JupyterLab) as a data scientist.
A bit about my background?
I studied Maths, Chemistry, and Biology in A-levels — traditional school-leaving subject-based academic qualifications offered by schools and colleges in England and Wales — in preparation for university, further study, training, or work. I picked these subjects because I wanted to work in the STEM industry with cutting edge technology that could help shape the future and make the world a better place.
Why did I choose this career path?
I was first introduced into the world of data science, along with its practical application in a global organisation when I started as a data analyst apprentice in a Data Science team at Haleon. At the time Haleon was the consumer healthcare business unit of GlaxoSmithKline.
Through this apprenticeship, I had the opportunity to work with different professional profiles in data such as data analysts, data scientists, data engineers, and many more. Amongst the various profiles, the role of data scientist stood out the most to me because of the constant learning and journeying through data that occurred every day. In addition, the chance to use mathematical techniques and algorithmic approaches to derive solutions to complex business and scientific problems appealed to me.
What do I do day to day?
As a junior data scientist, I start my day reviewing emails and Teams chats that I may have missed from the day before. I then open up Jira, a project/task tracking tool, to update the status of the tickets I’m working on and prioritise my tasks for the day.
I also participate in daily stand ups/scrums which are dedicated time for us to discuss status updates on the tickets we are working on for the project sprint. I find this helpful in ensuring that we are on track especially when working remotely, and also it gives me a chance to learn about what other members in the team are doing.
Sometimes I pair programme with more senior members of the team working on the same project with me. Pair programming is when two developers work together to tackle a single problem together, on one device. This is a great way for me to learn from more experienced data scientists and I always learn something new.
My day could also involve a 1-2-1 meeting with my line manager which gives me an opportunity to discuss career goals and any challenges or successes that I have encountered since our last catch up.
And of course, I also get to code and document! Depending on what the project team requires of me, I could either be coding to clean and prepare data; to conduct data analysis on a given dataset; to run, develop, and evaluate statistical and predictive models; or to create data visualisations in the form of dashboards or reports, all of these in parallel with the work that a senior data scientist I am working with is doing.
Are there any areas of DS/ML that I feel will be particularly prominent in the future?
I feel that within the area of data science and machine learning, natural language processing (NLP) is one of the most exciting fields in AI and will become prominent in the future. Everyday we use words to communicate within the business; to express ourselves in social media; to empower ourselves with knowledge when searching on the internet; and even to keep in touch with our friends and loved ones through text messages. The increase in email data alone since 2017 shows how much text data is being generated on a daily basis.
NLP has also already given rise to technologies like chatbots, translators, voice assistants, spam detection, auto-correct, auto-complete and many other tools that we use daily. As unstructured text data grows, NLP technology has also continuously improved to better understand the nuances, context, and ambiguities of human language (ChatGPT-3), which is why I think that it will become a prominent field in the future.
How do I keep up with the everything Data Science?
One thing that I love is that, because it is an interdisciplinary field, you can never run out of things to learn about. To keep with this ever-evolving field, I participate in our wider team’s Data Science Download sessions where internal and external speakers present on advanced DS/ML/AI topics. As a junior data scientist, I sometimes struggle in fully understanding the presentation, however, exposure to these topics gives me opportunities to delve deeper into the basics and then progress in my understanding.
As part of my data science degree apprenticeship, I keep up with and increase my knowledge via lectures conducted by Anglia Ruskin University and Cambridge Spark. I also expand my knowledge by reading research papers, LinkedIn Learning courses, and also YouTube videos, and setting up 1-2-1 meetings with senior team members who are specialising in a topic of interest. I also read technical and non-technical books and blogs to better my soft skills.
What do I like most about working at Haleon?
One of the things that I like most about working at Haleon is that I am constantly learning new business areas and processes. My team works on a variety of projects within the business areas including Quality & Supply Chain, Research & Development, Consumer & Expert, and Customer. This gives me the opportunity to work with various professionals with different backgrounds plus a wealth of experience and knowledge which cannot be learned from books alone. Through their willingness to share, I can develop my skills further. I relish the opportunity to continue learning from a skilful team that encourages and inspires personal growth, whilst working towards the same goal of making the world a better place with humanity at its core.
