Building a diverse and inclusive health data research workforce is important to ensure we beat cancer sooner, for everyone. Earlier this year we were pleased to host some incredibly talented Black data science interns. Here we find out how they got on…
Data science is becoming an incredibly important tool in cancer research. Data scientists and experts are increasingly working with other researchers to take a data-driven approach to the, now incredibly data-rich, fields of discovery and translational cancer science.
Black data scientists are very under-represented in the data science field, and so this year Cancer Research UK (CRUK) participated in the Health Data Science Black Internship Programme run by Health Data Research UK (HDR UK). Six CRUK funded groups hosted some very talented interns – and we caught up with some of them to find out what the programme was like for them.
While researching career prospects based in life sciences and technology, health data science stood out to me. The concept is truly fascinating as it interlinks various disciplines such as epidemiology and programming.
I had no experience in health data science and limited knowledge about cancer and so I was excited to find out what working in the field involved. For this reason, this internship seemed perfect for me.
I think it’s great that CRUK is inclusive of ethnic minorities interested in the sector. Being a black woman in STEM is quite intimidating and this internship helped boost my confidence. Being able to connect and work with other under-represented individuals, with similar career interests as me, was extremely rewarding and encouraging.
“It’s important for me to have a job that positively impacts individuals’ lives. This internship showed me that data science fits this description.”
I was hosted by CRUK Oxford Centre who made the whole experience amazing. I was given the opportunity to work with leading researchers in various disciplines within health data science such as mathematical biology and bioinformatics. This gave me a holistic view of what life as a data scientist is like. I was able to work on my own project which was focused on the stratification of colorectal cancer data. I created visualisations based on patient data using R code to find various relationships and trends. This was extremely challenging but helped improve my programming, analytical and critical thinking skills immensely.
I believe that the programme helped kick-start my career journey. I aim to work in a field that is never stagnant and is constantly expanding which can always challenge and excite me. Moreover, it’s important for me to have a job that positively impacts individuals’ lives. This internship showed me that data science fits this description.
Anastacia is a Biochemistry student at the University of Nottingham with an interest in epidemiology and disease. I have developed a newfound interest in technology and I believe health data research is a great combination of both fields. I am looking forward to learning more about the role of a health data scientist and connecting with individuals in the field.
Apart from my desire to gain real-world experience in data analysis, I thought the internship would be an excellent opportunity to explore health data science.
I am interested in this sector because I am keen to play a part in bringing about the transformation of healthcare through data insights whilst also adding diversity to the understanding of health data. That is why organisations like CRUK are supporting the internship initiative – to bring together a fusion of different backgrounds to provide solutions to tackle health challenges with data science.
My experience at CRUK was marvellous. I was able to take ownership of the project I was working on with lots of support from my line manager, mentor, and project manager. There were, of course, a few challenges when I first started. I was overwhelmed trying to familiarize myself with cancer data terminologies and setting up the right data science tools for the large datasets was tricky. But the friendliness of the CRUK Cancer Intelligence team and the office ambiance really made a difference.
I developed and applied machine-learning based models to predict the status of patients and their cancer using a PySpark Python API data analysis platform.
I also appreciate the importance of creating a scalable outcome regardless of the technological application and I have developed a real empathy toward my technical approaches, which have improved tremendously.
Kafayat is a computer science masters student at the University of Nottingham with interests in big data engineering and science.
I was hosted by the CRUK Cambridge Institute. Having no workplace or practical experience, I saw it as a great opportunity for me to learn from, and work with, leading researchers in healthcare using data science in their work. It was also great to have a taste of life as a health data scientist.
The internship helped me choose my career path and develop strong ties with people already in the industry. CRUK’s inclusion of diverse people, especially from under-represented groups, irrespective of their career stage in all areas will strengthen the knowledge base and give a real reflection of the population who are going to benefit from the findings of the research. I was really pleased that during my internship I was able to make meaningful additions to my team.
“The experience I have had, and the interest I have developed is like a new chapter in my life.”
Without prior knowledge in cancer, I was concerned whether I’d be able to learn cancer terminologies and apply my data science knowledge in my new workplace. However, this proved not to be an issue because of the great structure put in place by the group leader. I had supervisors and mentors who helped me to embrace my new working environment and the novel technologies.
I improved my computational and programming skills and received great guidance on leadership and personal development. Before joining the team, I was less confident and dependent on other people to give me direction, but even after the short time I spent with the CRUK team I am more confident in what I do and eager to work and collaborate with different people.
The experience I have had, and the interest I have developed is like a new chapter in my life, and I am hoping I can continue working with CRUK soon.
Phinehas is an MSc Applied Data Science student at Teesside University. He is hoping to use his skills and knowledge to harness the use of data science in healthcare research for the benefit of all.
So, I am not much of a writer, but here goes!I applied for the internship whilst I was working with data – but this just involved queries on databases rather than health analytics or research. So, I was really excited to take my knowledge to the next level.
From the interview with Cambridge University and a discussion around the desire to build an advanced model to identify chemical names, diseases, and other variables that identify cancer markers, I was blown away at the level of work undertaken in the team.
Fields of data science like natural language processing and predictive analytics, that I had previously enjoyed, were being used here on a large scale and that was really exciting to me. That was especially true because the work actually mattered – it was going to help improve the overall health of people, not to mention actually help save lives. This was a project I could not wait to start, and I was honored to partake in an opportunity that helped redefine how searches can be made on health data.
It was a privilege to work with the great minds I met, and it is an experience I hope more people can have.
Fisayo is a graduate of big data analytics from Birmingham City University. She wants to make a lasting change in health analytics in less privileged communities.
Health Data Science Black Internship Programme recruitment for the 2023 intake is now open.
If you’d like to be a host organisation read more here.
If you are interested in being an intern check out some details here.
To find out more about what we’re doing in data science, read our research data strategy.