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Data Science with 1+ years in Machine Learning & AI
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Assessing your cultural and operational fit
Final-year MSci Physics student at UCL with hands-on experience in Python, machine learning and data analysis, developed through academic research and a summer internship. Holds a CITA certification in AI Ethics and Regulations, committed to responsible AI development. Eager to apply data science skills in a collaborative, entry-level AI and data science role.
University College London
MSci Physics · Physics
August 1, 2022 – June 30, 2026
Taylor's College, Sunway
Cambridge A-Levels · Physics, Mathematics, Further Mathematics, Chemistry
June 1, 2021 – May 31, 2022
Taylor's International School Puchong
IGCSE · Physics, Mathematics, Additional Mathematics, Chemistry
June 1, 2017 – May 31, 2020
UCL INSTITUTE OF MATERIALS
Summer Intern
July 1, 2025 – September 1, 2025
London, England, United Kingdom
Introduction to AI Ethics and Regulations
CITA
June 1, 2026 – Present
Understanding Machine Learning
DataCamp
June 1, 2026 – Present
End-to-End Machine Learning
DataCamp
June 1, 2026 – Present
Pre-processing for Machine Learning using Python
DataCamp
June 1, 2026 – Present
Qiskit Global Summer School
IBM
June 1, 2026 – Present
Introduction to Equality, Diversity, and Inclusion
University College London
June 1, 2026 – Present
Taylor's College Top Achievers Award
Taylor's College
January 1, 2022 – Present
Cultural Fit Analysis
The candidate's involvement in various student groups and leadership positions (UCL Women in Physics Group, UCL Physics Society, IBM Qiskit Fall Fest Marketing Lead) demonstrates a proactive, collaborative, and community-oriented mindset. The pursuit of a CITA certification in AI Ethics and Regulations, along with an 'Introduction to Equality, Diversity, and Inclusion' certification, indicates a strong commitment to ethical considerations and diversity, which are positive indicators for cultural fit within a progressive organization. The academic background in Physics, while not directly Data Science, provides a strong foundation in quantitative analysis and problem-solving, suggesting adaptability and a broad skill set. However, the experience is primarily academic and internship-based, which might require some adjustment to a corporate environment.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills through leadership roles in student societies (UCL Women in Physics Group, UCL Physics Society) and marketing lead for IBM Qiskit Fall Fest. These roles highlight dynamic and team leadership, inter- and intra-personal communication, critical thinking, and collaboration. The candidate's commitment to responsible AI development, as evidenced by the AI Ethics certification, aligns well with modern operational best practices. The academic background in Physics suggests strong analytical and problem-solving capabilities, which are crucial for a data science role.