• 🎓 I’m a final-year Statistical Science student at University College London.

• 🌱 Alongside learning data science and machine learning as part of my course, I have actively sought opportunities to gain real-world exposure to the application of technology and data in industry. Through spring and summer internships, I have built a solid foundation in Python, relational SQL databases, and YAML configuration files, and gained familiarity with JavaScript, HTML, CSS, and the Django web development framework. I am also proficient in using the Requests library to download data via API endpoints and in using Selenium automation to ethically scrape data from websites.

• 💼 My industry experience includes interning as a software/data platform engineer aligned with the Commodities and Global Markets division, which broadened my skillset in data analytics workflows and DevOps (where I worked extensively with Kubernetes and cloud deployments involving EKS, Argo Workflows, and ArgoCD). I also engaged directly with our clients, where I developed an understanding of various assets in the commodities, fixed income, and FX markets. My attention to detail was commended as excellent when I clarified requirements with clients to ensure the data pipeline I was building delivered exactly what they needed.

• 📖 Key modules I have taken: Statistical Machine Learning, Stochastic Processes, Algorithms and Data Structures, Applied Multivariate and High-Dimensional Methods, Bayesian Statistics, Stochastic Calculus, Linear Algebra, Probability and Statistics.

• 👯 My hobbies: Choir Singing, Yoga, and Painting

• 😄 Pronouns: She/Her

Please feel free to reach out and connect :)