Ibrahim Animashaun

Research Data Scientist Ibrahim Animashaun was the first intern placed at the Turing as part of Health Data Research UK’s (HDR UK) second black internship programme

Tell us about yourself and your experience prior to your internship? 

I have a medical background and have always been interested in how technology could be used to improve healthcare. Around three years ago, I started my journey into data science by learning Python - I remember how excited I was when I wrote my first program ‘Hello world!’. 

How did you get involved with the Turing? 

My journey into data science led me to the exciting opportunity to be involved in the HDR UK’s second black internship programme. This is one of several steps they are taking to give black data scientists, a heavily under-represented group, the chance to be involved and flourish in the health data science sector. Interns are matched to various host organisations, and I was delighted to have been be welcomed and supported by The Alan Turing Institute. 

Tell us about your experience during your internship, which team and projects did you work on? 

I had the opportunity to work as a research data scientist with the Research Engineering Team (REG) (a team of about 40 research data scientists and software engineers).  

I worked on a project exploring the use of synthetic data generators. This offers a way to generate realistic (but not real) patient data and associated health records in the OMOP (Observational Medical Outcomes Partnership) data models format using Synthea, an open-source patient generator. As a result of privacy and legal issues, healthcare data is difficult to access - synthetic data is useful to help enable data science experiments and machine learning applications.  

During the internship, with a lot of effort from myself, help from team members, my project team lead - May Yong, my line manager - Iain Stenson, my mentor - Markus Hauru, and Martin O’Reilly, Director of Research Engineering at the Turing. I developed technical and personal skills that will be extremely beneficial in my career

I had a very rewarding experience working at the Turing and it will certainly help my future in the field of health data science. I am grateful to have been given this opportunity to sharpen my job skills in this field and the chance to work for such a wonderful organisation.  

What was your most memorable experience in your time with us? 

The most memorable experience was attending the RSECon 2022, the sixth annual conference for Research Software Engineering. There were interesting talks and enlightening workshops. I met people from different organisations, the dinner was amazing and the show at the dinner was just incredible.  

The theme for this year's Black History Month is Time for action, how would you recommend us attracting diverse backgrounds, particularly from the black community, to research roles at the Turing? 

Attracting people from diverse backgrounds must be intentional and the Turing has made efforts in this regard with the Equality, Diversity and Inclusivity (EDI) strategy and action plan launched in September 2021.  

It is crucial to focus on growing the existing diverse talent in the Turing. If you can effectively nurture and promote diversity within an organisation, minorities will see it as an excellent place to work and will apply for open positions. Also, recruitment teams must actively seek out diverse candidates. One approach is to encourage diverse employees within the Turing to refer their connections. Creating a diverse candidate referral program is a great way to boost diversity. 

Finally, demonstrating the diversity already in the Turing is important to attract talents from diverse backgrounds,. This could be achieved by having a diverse interview panel for the interview process and displaying pictures that show the diversity at the Turing in places accessible to the public, for example the Turing’s website. A picture is still worth a thousand words. These could have far-reaching effects in encouraging people from a range of backgrounds to apply to the Turing.