London Area, United Kingdom
Solutions engineering - Client Delivery and Execution
TempThreads — AI-powered outfit intelligence, built for real weather TempThreads is a smart mobile app that tells you what to wear based on how it actually feels outside, not just the temperature. We combine real-time weather data with personal style preferences and comfort feedback to deliver practical, personalised outfit recommendations every day. What it does: Layering guidance, material suggestions, umbrella and windproof alerts, 7-day outfit outlooks, and travel-aware packing lists, all tailored to you. What makes it different: The app learns from your feedback. Over time it adapts to your comfort thresholds, style preferences, and daily routine to improve every recommendation. Built with: Flutter, Firebase, GCP, and Gemini; designed cross-platform from day one with a focus on personalisation, scalability, and clean UX. Where we are: Currently in stealth with an active client partnership, iterating based on 1,500+ A/B experiments and real user feedback. 🚀 Coming soon to iOS, Android, and web.
I coach 3 times a week in primary schools, teaching chess to kids and managing a classroom. FIDE rating -1903
During my 12-week internship, I contributed to the production of the Department’s official Bus Statistics , supporting their development, analysis, and publication. I worked extensively with BigQuery, RStudio, Python Notebooks, Excel, Looker Studio, and GitHub, carrying out data analysis, quality assurance, and automation of workflows. I also responded to public policy queries and reviewed publications to ensure they were accurate, accessible, and compliant with the UK Statistics Authority’s Code of Practice. A major part of my role was leading the validation process for the Annual Bus Operator Survey, liaising with operators across the UK to ensure reliable data. I automated aspects of the imputation process for missing responses and developed a personal project using cosine similarity to evaluate the accuracy of imputation against actual survey data. To support colleagues and policymakers, I designed a user-friendly interface that made results and insights easy to explore and apply to decision-making. Alongside this, I collaborated in an agile team environment, using Loop to track tasks and GitHub for version control, pull requests, and repository management, ensuring transparent and reproducible workflows. This experience gave me end-to-end exposure to statistical production, from raw data handling and validation through to publication and dissemination. I really enjoyed my time in the civil service and such tables references are attached here: https://www.gov.uk/government/collections/bus-statistics
During my internship, I focused on data analytics, database management and visualisation on Microsoft Power BI. I spent my time learning Google BigQuery to deliver and update the data to the Power BI dashboards to create reports. For these reports I learnt a lot about DAX and created necessary measures and slicers for the insights team of Xiatech to be then published for the client. This experience helped me enhance my knowledge of google services like Cloud and Bigquery to understand different roles in the company and how important it is to the backend. . Finally throughout this whole experience, understanding how to use and plan tasks out using Jira whether it is through agile or scrums to organise ourselves and groups.