Annabelle and Sonia
Sonia (left) and Annabelle (right) tell us more about what it's like to have a career in data science.

Today we are celebrating the International Day of Women and Girls in Science, so we asked Sonia Sharma and Annabelle Macleod to tell us a bit about their roles at OPEX and their route into a career in data science.

Q: When did you both realise you had an interest in data science?

Sonia - After completing my qualification in Maths and Computer Science I wanted to pursue further studies. I attended an open day at Robert Gordon University, and after interaction with different departments, I realised that data science was the best suitable career option for me.

Annabelle - I started my career as a molecular biologist and I have always been interested in science and figuring out relationships between various observations. Around 7 years ago I decided to switch career, but I was still interested in staying on a STEM path.

At the same time, data science was getting a lot more attention and more industries were interested in utilising the data that was being produced daily, so I saw a career in data science as something that would allow me to merge my interests in science with new technologies while also opening new doors with regards to my career.

Q: What did you study at university?

Sonia - I studied a Master’s in Data Science which included; data warehousing and mining, advanced data management, information retrieval systems, big data analytics, visualisation, data science development and research.

A significant part of my studies was learning about data capture and cleaning and conformation solutions using SSIS, SSAS, SSRS, SQL server, MDX, and Tableau. The subjects that could potentially lead to a career in data science are maths, statistics, and computer science.

Annabelle - I first studied applied biosciences and chemistry, then specialised in molecular biology, I worked as a researcher for several years but then went back to study computing science full time.

I would say any scientific discipline provides a good background to move into data science as long as someone is willing to learn the necessary computing knowledge (there are a lot of online resources), conversely, someone with a strong computing background but also interested in figuring things out would also make a good candidate.

Q: Have you noticed an increase in women entering the industry?

Sonia - Yes, I have noticed a positive increase in women entering this industry. There are so many opportunities after gaining the relevant experience. It can give women options to maintain a delicate balance between their personal and professional life whilst providing them with a challenging but progressive career path.

Annabelle - It may have been because my course was a computing course rather than a specialised data science one, but unfortunately I was one of only two girls by the time I reached the last year out of around 30 people. It is possible that there is a difference even over the last few years, I hope so.

Q: Tell us about your role. What does it involve?

Sonia - As a Data Scientist, my role is to explore, analyse and visualise data. I build dashboards and tools using different computer languages and techniques. I use predictive analytics and apply machine learning techniques to discover more about the data collated. I am also involved in research and development projects.

Annabelle - I analyse data coming from offshore assets: every day the data we receive is fed into statistical models which allow us to detect anomalous trends or events. Together with the data analysts on the team, who provide specialist knowledge, we can then determine if the event is significant and needs to be relayed to our customers.

We aim to help our customers detect potential issues before they arise and become costly. We also do more targeted studies where we will help our customers identify the approach of a specific event using machine learning techniques. No two days are the same and it is very collaborative, which makes it very engaging. There is also a creative side to it in order to come up with strategies suited to a specific problem.

Q: How can we encourage more people into data science?

Sonia - By improving awareness of the opportunities - as data is the future.

Annabelle - Public engagement events might be a good way to showcase what we do, as I think most people will have heard the term but will be unsure of what it means on a day-to-day basis.

Q: Why is data science in the oil and gas industry so important?

Sonia - Data science is important in our industry because it helps manage vast datasets and improve exploration and production efficiency. Through new insights we can boost production performance, help to optimise operations, lower costs and gain a competitive edge.

Annabelle - The industry is currently facing a number of challenges such as wells that are producing less in some areas and the drive for reducing emissions. Data science can help the industry understand some of its issues better or identify underlying causes to problems, helping to achieve more stable producing conditions. Techniques such as machine learning will also help anticipate adverse events before they arise.