Data Science Internship

1. You have completed your bachelor's degree in engineering, computer science, mathematics, or a related quantitative field

2. You’ve demonstrable experience working with time series forecasting techniques and libraries (pandas, scikit-learn, statsmodels, TensorFlow/PyTorch, MLflow)

3. Prior experience working with energy data, smart meter data, or IoT sensor data is highly preferred, but not a must-have

4. Strong programming skills in Python with experience in data manipulation, statistical analysis, and machine learning

5. Someone who thrives on experimentation and can work independently while collaborating effectively with technical teams

6. Available to start on short notice and eager to work in a fast-paced, innovative environment focused on solving one of the most pressing problems preventing climate change

Where you'll work and how you'll contribute:

1. Support the development of a new product line that we're launching soon, where the forecasting models you build will be a core component

2. Solve real-world problems in demand-side management and help the energy transition by preventing the need for rapid grid capacity expansion through accurate energy demand predictions

3. Work collaboratively with a cross-functional team comprising software engineers, product managers, data scientists, and building physics and energy experts

1. Develop and experiment with multiple time series forecasting models to predict building energy demand patterns

2. Analyze smart meter data and building performance metrics to identify key features and patterns that influence energy consumption

3. Implement and compare various forecasting approaches (ARIMA, XGBoost, Prophet, etc.) to determine the optimal modeling approach

4. Conduct data preprocessing, feature engineering, and model validation to ensure robust and accurate predictions

5. Create visualizations and reports to communicate model performance, insights, and recommendations to stakeholders