Urs A. Hurni

Geneva, Switzerland ualh@proton.me

Hi!
I’m Urs, a Swiss native and data enthusiast who loves turning complex problems into elegant and meaningful solutions..
I enjoy solving complex problems, exploring innovative solutions, and constantly learning.
My work experience as an Analyst and my background in Business Analytics, Economics, and Management, have taught me the art of turning data into impactful decisions I’ve worked on projects that range from predictive modeling to strategic analysis. I enjoy bringing ideas to life with data and helping teams achieve their goals.
Feel free to dive into my projects or connect. Let’s create something impactful together!

Projects

Crypto Sentiment

Technology Used : Python, HTML, CSS

This project is a Flask web application that integrates various APIs to analyze cryptocurrency news sentiment and its impact on market prices. The app fetches real-time data, performs sentiment analysis, and displays trends through an interactive dashboard. It uses machine learning techniques such as Linear Regression, Random Forest, Gradient Boosting and Support Vector Machine as well as several resampling methods in order to analyse the impact of sentiment on price of different crypto currency.

View Project View Programming Report View Data Analysis Report

Binance : Doing Business in China

Academic Paper

This academic paper explores how the Chinese company Binance conducts s business in China, detailing its development and the challenges it has faced. Presented as part of a lecture series for the "Doing Business in China" course by Tomas Casas Klett in April 2022, the paper delves into various aspects of Binance’s operations. It examines strategic decisions, such as setting up in Hong Kong, regulatory challenges, and the tightening grip of Chinese authorities on cryptocurrency activities. The paper also discusses the broader implications of these regulations on Binance's future in China and globally, highlighting the company’s strategic adaptability in the face of evolving international regulations

View Paper

Predictive Peaks: Leveraging Machine Learning for Swiss Property Insights

Technology Used : R

This project uses machine learning to predict real estate prices in Switzerland, using data from ImmoScout24 and Swiss Federal Statistical Office. Techniques like Linear Regression and Random Forest are employed, with a focus on model accuracy and local market trends. Key predictors like property size are identified, suggesting potential for broader applications in real estate decision-making.

View Project

Energizing Change: Electric Vehicle Rise in Switzerland

Technology Used : R

This study explores electric vehicle (EV) adoption trends in Switzerland, investigating factors like regional differences, demographic influences, and comparisons with France. It uses diverse datasets, including vehicle registrations, oil prices, demographics, Google trends, and political affiliations. Key findings include a rise in EV registrations, variations in adoption rates across regions and demographics, and the influence of charging station availability. The analysis also highlights the role of political dynamics in EV adoption. Limitations include the lack of detailed pricing data and the unexplored impact of marketing and government subsidies. Future research could delve into these aspects for a more nuanced understanding.

View Project

Zurich and Vaud by the Numbers - Predictive Insights into Tourism Dynamic

Technology Used: R

This project aimed at forecasting tourism trends in Switzerland. Techniques such as Linear Regression, Random Forest, ETS, ARIMA, and TSLM models were employed to analyze and predict overnight stays of visitors in Vaud and Zurich. The project showcased the impact of global events like the COVID-19 pandemic on tourism, emphasizing the importance of adaptive forecasting and strategic planning in the tourism sector.

View Project

Lait Equitable: A Data-Driven Approach to Fair Trade milk

Technology Used: R

The following project was the done with the collaboration of an association 'Lait Equitable' which provides fair trade milk in Switzerland. The goal of this project is to analyze the sales and identify trends and patterns in the data that can help us better understand the production of fair trade milk in Switzerland. We will use a variety of data analysis techniques, including exploratory data analysis, data visualization, and statistical modeling, to analyze the dataset and draw conclusions about the production of fair trade milk in Switzerland.

View Project

IT-Tools

Programming Languages & Tools

Interests

Outside of my professional pursuits, I am passionate about staying active and continually learning.
During the winter, I enjoy outdoor activities like backcountry Freeriding, which has taught me how to manage risk, resilience, and adaptability.
In the warmer months, I take on challenges such as hiking and cycling, pushing myself to explore new heights and build endurance.

Indoors, I enjoy creative and detail-oriented activities such as crafting and design, which foster focus and innovation.
I am also deeply motivated by the potential of using data to address real-world challenges and support impactful causes, particularly in humanitarian and development contexts.