Lewis Sword
University:
Queen Mary University of London
Placement:
MeVitae
Role:
Machine Learning Engineer/data scientist
“Having worked on projects that use the latest innovations in machine learning, the MeVitae placement serves as an excellent addition to my CV and has helped prepare me for future roles.”
Describe a typical day:
A typical day involved working with Python to implement tasks discussed with the MeVitae tech team. My main responsibilities focused on acquiring and analysing text data, understanding its structure, and applying algorithms to extract relevant information. A key part of my role was identifying specific "section" elements in CVs. We began with a pretrained transformer model and fine-tuned it using section-labeled data. By analysing the outcomes, we frequently experimented with different techniques, such as masking word tokens and applying sentence-level binary classification.
Why did you decide to do a placement?
Given my background in physics and my aim of building a career in data science, a placement was an excellent opportunity to bridge the gap and gain practical experience. It was especially important to observe how projects are executed in industry settings and to increase my familiarity with coding standards and practices.
How do you think doing a placement has benefited you for the future?
I think it has provided a huge benefit in terms of future possibilities. My PhD in physics has prepared me for many aspects of data science, but experience in an industry environment is also important. Having worked on projects that use the latest innovations in machine learning, the MeVitae placement serves as an excellent addition to my CV and has helped prepare me for future roles.
What are your next steps?
I intend to continue my journey in data science. It has been fantastic to further my understanding of natural language processing, and I have also gained experience in general machine learning practices. Based on the internship and my personal interests, I am looking toward data science consultancy roles since they offer the opportunity to work with a variety of data and to develop solutions for clients.
