Daniel Elston

I am a Data Scientist with nearly 1.5 years of industrial experience. I hold an MSc in Data Science and AI, and a BSc in Physics.

I started my academic career with a Physics degree from the University of Bristol, achieving a 2:1. My final year industrial group project gave me the chance to work with CERN, developing a particle beam loss detection device for deployment in the LHC. Our report was awarded a commendation.

I pursued further studies in Data Science and AI at Queen Mary University of London. I achieved a high Merit and again, went on to complete my dissertation in industry, developing a Dynamic Pricing algorithm.

My academic work saw me develop skills in Python, Git, SQL, Machine Learning, Deep Learning, Data Engineering, Statistics, creative problem solving and communication to name a few.

Post graduation, I have worked at a consultancy as a Data Scientist, providing services to the UK MOD. In this position, I've been involved with many aspects of the data lifecycle, from data engineering to implementing machine learning solutions. I have further worked closely with various stakeholders.

Outside of my day job, I enjoy working on side projects which can be found on my GitHub and have recently begun writing Data Science, or tech-focused blogs.

• Tech Stack: Python, SQL, Git, LaTeX
• Libraries: Pandas, Numpy, Matplotlib, PyTorch, Tensorflow, Opencv, PySpark, nltk, gensim
• Computer Vision, Time Series Forecasting, NLP, Object Orientated Programming
• Machine Learning, Deep Learning, Data Engineering

• Physics: University of Bristol - Final year industrial group project: Built a beam loss detection device for rapid deployment in the LHC (CERN)
• Data Science and AI - Queen Mary University of London: DIssertation included an industrial data science consultancy placement where I built a dynamic pricing algorithm end-to-end for a leading distributor of car parts (across the UK and Europe).