Hello and thank you for your visit.
I have a dual master’s degree in mechanical engineering and management/ entrepreneurship. I worked as a visiting scholar at UC Santa Barbara and UC San Diego, then I was a Solar Project Manager with EDF Renewable Energy in Paris, France, and more recently with Pristine Sun in San Francisco, California, for a total of 7 years of experience in the Renewable Energy industry.
Over the years, I developed a strong interest in the “Internet of Energy”, including: Smart Grids, Energy Storage, Demand Response, Data Analysis and Machine Learning.
After completing relevant online courses and projects (see below), I decided to focus my career on Descriptive and Predictive Data Analytics. Depending on the offer, I could consider a different industry than the energy sector.
- Challenges: 3rd prize at Engie DataPower Hackathon (July 2016), Kaggle and Datascience.net projects
- Web development: design and coding of a website featuring a personalized recommendation engine for cooking recipes (nicolasguillaume.pythonanywhere.com), programmed in Python/Flask/Numpy/Scikit-Learn/NLTK
- Creating a smart power meter, detecting devices, and analyzing usage patterns (Project)
- Online courses:
- Machine Learning (Stanford University – Coursera)
- Exploratory Data Analysis with R (Udacity)
- Foundations of Marketing Analytics (ESSEC Business School – Coursera)
- Foundations of Strategic Business Analytics (ESSEC Business School – Coursera)
- Digital Analytics Fundamentals (Google Analytics)
- SQL (Stanford Online)
- A/B Testing (Udacity)
- Statistical Inference (Johns Hopkins University – Coursera)
- Statistical Inference (Udacity)
- Descriptive Statistics (Udacity)
- Project (4-month internship)
- Predicting the demand of a bike sharing system
- Online course
- Introduction to Data Science (University of Washington – Coursera)
- Python (Codecademy)
Feel free to contact me (via LinkedIn) with any questions.