Analytics Engineer | SQL, Python, dbt, Power BI
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I am a Data Engineer with a first-class MSc in Mathematics from Queen Mary University of London. With a deep passion for problem-solving, logical reasoning, and statistical analysis, I excel at transforming complex datasets into actionable insights. I specialise in optimising data architectures, building efficient data models, and leveraging data to drive business decisions.
Skilled in SQL, Python, dbt, and Power BI, I am eager to apply my expertise to solve real-world challenges and contribute to data-driven organisations.
iO-Sphere, London – Data Analyst, August 2024 – Present
Immersive data analytics and engineering training programme
● Completed an intensive 10-week data training programme, gaining advanced technical skills in statistics, SQL, Python, Power BI, and dbt.
● Worked with over 500 million rows of data from a fictional e-commerce company called Prism, translating complex datasets into strategic business solutions.
Queen Mary University of London – Mathematics Research Intern, May 2023 – August 2024
School of Mathematical Sciences Undergraduate Internship with Dr Anna Maltsev
● Carried out research in Random Matrix Theory and studied spectral properties of different matrix classes
● Analysed the Matrix Dyson Equation for correlated square matrices and extended the model to a general rectangular case
● Utilised Mathematica Software to perform a stability analysis on the rectangular case
Queen Mary University of London – Student Ambassador, January 2022 – May 2023
Representing Queen Mary and championing education
● Represented the university at over 10 Higher Education Fairs, advising and supporting prospective students and their parents with application processes
● Delivered presentations to over 200 school pupils on key topics, such as effective study strategies and budgeting tips, helping to increase engagement with university outreach programs
QUEEN MARY UNIVERSITY OF LONDON – London, UK
2019 - 2023
MSci (Hons) Mathematics, First Class Honours
iO-Sphere, Data Analytics Programme
August 2024 – Present
