Master Thesis Project 2018: Data-mining of production locations using social media sites and open source maps
Use data-mining techniques to obtain information about the global distribution of companies using large social media sites and open source maps (OpenStreetMap).
Climate change is currently gaining increasing attention in the financial industry, with an increasing need to quantify climate risks and factor them into investment decisions. A crucial component of climate risk modeling is information on the global distribution of companies’ physical operations. However, companies rarely disclose such information to the public. We want to use data-mining on corporate websites, social media accounts and open source maps to create a methodology through which the global distribution of company production sites can be uncovered.
The information will directly feed into core components of Carbon Deltas model, and potentially improve the reliability of climate Value-at-Risk calculations. The calculations are applied on more than 20,000 companies and the data is used by investors to guide investment decisions.
Phase 1: You work with our analyst team to examine available corporate social media pages through which information can be extracted.
Phase 2: You work with our data science team to create a first data-mining model to derive the production locations of the largest publicly traded companies and benchmark your results against real production location data.
Phase 3: You work with our software development team to create an implementation plan for the model developed in Phase 2. Step by step, you transform the idea to software.
Finalization: In the final weeks, you analyze and share your results.
You can experience all phases of a typical data science project, together with a fun & smart team. For this project, expect a steep technical learning curve.
ABOUT CARBON DELTA
CARBON DELTA is a young environmental fintech startup located in Zürich Seefeld, right next to beautiful Lake Zürich, 10-min walk from Bhf Stadelhofen / Bellevue. We build cutting-edge software models to identify and analyze the exposure to climate change of publicly traded companies. Our goal is to alert investors of the climate risk profiles of companies and to tackle climate change at the roots. This is a bold mission and we are always looking to learn from research conducted by our students.
We are happy to support motivated students with practical support and academic guidance throughout their projects. Students can choose their project from a broad range of topics, and can shape it. We would like to hear about your ideas!
OUR TECHNOLOGY STACK
- Python 3
APPLY WITH US IF
- You would like to use your thesis/internship to do applied research with real-world impact.
- You like working hands-on with environmental, economic, and financial data.
- You like to develop and enhance mathematical models.
- You like to receive guidance and input to your research from a dedicated, technically savvy developer team (Ph.D. level, ETH Zürich).
- You would like to gain insight in the work of an exciting and successful start-up.
- You like to create and interpret advanced data visualizations.
PLEASE APPLY WITH
- a compact CV.
- the proposed topic of your project, together with with your motivation.