About
I’m Logan, a final-year Politics and Data Science student at the London School of Economics. I grew up in Toronto and now live in London.
I build data tools and analysis: machine-learning forecasts, optimisation models, data pipelines and web apps. The field I most want to apply them to is transport and urban planning, because the way cities are planned shapes how people live.
My projects reflect both sides. Some are analysis, like mapping where London’s roads are most dangerous; others are software, like BLACKOUT, a no-spoilers World Cup site I built end to end.
Outside work, I build puzzles, snowboard and play trivia.
Experience
Business Intelligence Advanced Analyst, Bell Media
Toronto, summer 2026 (internship)
At Canada’s leading media company, I built a self-updating tool that chooses which NFL game each station airs: machine-learning forecasts (XGBoost) feed an exact mixed-integer program (PuLP and CBC) that maximises total audience under carriage rules, run from Excel by colleagues who don’t code. I also automated the collection of rival TV schedules with a Python pipeline and an AI agent, and presented a case study to TSN’s programming team. Read more about my work at Bell.
Education
London School of Economics and Political Science
BSc Politics and Data Science, 2023 to 2027
Skills
- Machine learning and statistics
- XGBoost, scikit-learn and regression modelling, with forecasts validated on unseen data
- Optimisation
- Mixed-integer programming with PuLP and the CBC solver
- Data engineering
- Python pipelines with pandas, web scraping with Scrapy, SQL, SQLite and MongoDB
- Geospatial analysis
- GeoPandas, sf and Folium
- Web development
- JavaScript, Node.js, HTML, CSS and Streamlit
- Tools
- R (tidyverse, ggplot2), Git, Quarto, and Excel with VBA, Power Query and COM automation
- Languages
- English and conversational French
Contact
Email l.b.daniels@lse.ac.uk, or find me on LinkedIn and GitHub.