Forecasting Engineer

Key Skills

AWS, Data Analytics, Data science techniques, Machine learning techniques, NumPy, Pandas, Python Programming, PyTorch, TensorFlow, XGBoost

Job Description

Geli (Growing Energy Labs, Inc.) provides software and business solutions to design, connect, and operate energy storage systems ranging in size from residential to utility-scale, as well as grid-tied, microgrid, and off-grid systems. Geli’s suite of products creates an ecosystem where project developers, OEMs, financiers, and project operators can deploy advanced energy projects using a seamless hardware-agnostic software platform.

Geli is a subsidiary of Hanwha Q CELLS, one of the world’s largest photovoltaic manufacturers most recognized for its high-performance, high-quality solar cells and modules.

OUR VISION

Geli is committed to helping make the planet a cleaner, better place to live, both with our software products and through our everyday actions.

Imagine a world where there is less reliance on non-renewable power, where you source your electricity from your neighbors rather than from power stations hundreds of miles away and software makes the best possible use of the solar, wind, and battery storage available. This is our vision.

We are looking for enthusiastic colleagues that are not only fluent in technology, but also share our vision of a world running on 100% renewable energy.

ABOUT THE JOB

Geli is looking for an experienced Data Scientist with software development experience in Python to join our Data Science team. Your primary responsibility will be to lead the development of our time series forecasting models for solar and energy consumption using machine learning techniques, but you will also help develop new forecasting models as various needs arise (eg: prototyping forecasting wholesale prices for a new market). Our data analytics and cloud platforms use state-of-the-art technologies to set you up for success. As data science is at the core of Geli, you will have plenty of opportunities to contribute to the software development of our other energy storage products. As a member of the team you will have significant influence on the direction of our technology stack.

We are looking for a motivated self-starter that thrives in a dynamic environment. Having a strong work ethic with excellent problem-solving skills is equally important as being a team player who enjoys learning and teaching.

You will work closely with software, analytics, and optimization engineers focusing on the duties listed in Primary Responsibilities.

PRIMARY RESPONSIBILITIES

• Lead the development of our time series forecasting algorithms, which includes:
• Feature engineering
• Prototyping new algorithms
• Benchmarking performance across various load profiles
• Integrating new forecasting algorithms into our production code base with robust test coverage
• Collaborate with the rest of the team to assess how forecasts can be adjusted for various economic objectives.
• Proactively identify opportunities within Geli that can benefit from data science analysis and present those findings.
• Work collaboratively in a diverse environment. We commit to reaching better decisions by respecting opinions and working through disagreements.
• Gain in depth experience in an exciting industry as you work with storage sizing, energy financial models, energy tariffs, storage controls & monitoring.

MINIMUM QUALIFICATIONS

• 2-3 years experience as a Forecasting Engineer, Data Scientist, ML Engineer or Statistician
• Statistical Forecasting: Proficient in Statistical Forecasting Techniques (e.g. SARIMA), including multivariate and multi-seasonality modeling
• ML algorithm development: Proficient in hyper-parameter tuning techniques, online training & prediction set-up and performance evaluation
• Data Science Skills: good understanding of supervised & unsupervised learning and performance metrics
• Programming skills: Proficient in Python (object-oriented programming)
• Python libraries: Pandas, Sklearn, Statsmodels, NumPy

PREFERRED QUALIFICATIONS

• Data Science Skills: model explainability modelling (SHAP, Lime)
• Python libraries: TensorFlow, PyTorch, XGBoost, LightGBM, SciPy
• MS or PhD degrees in Data Science, Computer Science, Statistics, Engineering, Science
• Previous experience in Power Markets, Energy Arbitrage, etc.
• ML deployment experience: Productizing code in integrated software systems and Cloud (AWS) deployment experience

BENEFITS OF WORKING AT GELI