Senior Data Scientist

San Francisco, CA /
Data Science /
Full Time

Are you excited about machine learning? Want to contribute to a more sustainable future? Myst is a startup that uses artificial intelligence to help energy companies better predict the future, to increase renewable energy adoption and reduce carbon emissions. We are building a platform that helps companies to create highly accurate forecasts at unprecedented scale. 

We recently closed our Series A round from two top Silicon Valley VCs. We are now looking for a Senior Data Scientist to join our team of eight in San Francisco. You’ll be joining a group of people committed to positive environmental impact from a wide set of backgrounds, ranging from academia and nonprofits to technology companies like Google, Apple, and Nest. 

Who are we looking for?

As a Senior Data Scientist you’ll play a key role in our core data science team. You will develop our data science capabilities and apply state-of-the art machine learning techniques on real-world energy forecasting use cases. We’re looking for someone full time with at least three years of experience in a world-class data science or software engineering environment and a proven record of being an effective collaborator.

Our current data science team is well-versed in a variety of data science techniques and has a deep understanding of energy forecasting use cases. As a startup, we're always tackling new challenges, so we prioritize candidates who learn quickly and make wise decisions across a variety of domains. Our current technical stack is Python, where we leverage open source packages, such as TensorFlow, Scikit-learn, and XGBoost. Our infrastructure is hosted in Google Cloud Platform, where we frequently run large scale AutoML experiments.

What might you be working on?

    • Collaborating with our business development team on solving real-world forecasting use cases for energy companies
    • Presenting the results of your own data analyses directly to our clients
    • Studying novel time series forecasting approaches from research environments
    • Improving and streamlining our existing data science workflows
    • Contributing to our AutoML approach for time series forecasting

Minimum Qualifications

    • Minimum of 3 years of work experience in data analysis related field, including expertise with statistical data analysis of time series data
    • Proficient software development experience in Python 2.x or 3.x
    • Experience with statistical packages in Python (e.g. TensorFlow, Scikit-learn, XGBoost, Pandas, Numpy) and database languages (e.g. SQL)

Preferred Qualifications

    • M.S. degree in a quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Physics, Electrical Engineering) or equivalent practical experience
    • Experience articulating and translating business questions and using statistical techniques to arrive at a solution using available data
    • Demonstrated leadership and self-direction, and willingness to both teach others and learn new techniques
    • Demonstrated skills in selecting the right statistical tools given a data analysis problem
    • Effective written and verbal communication skills
    • Deep understanding of state-of-the-art machine learning techniques such as gradient tree boosting, recurrent neural networks, autoregressive neural networks
About Myst

We are passionate about Myst because we use state-of-the-art technology to increase renewable energy adoption and reduce emissions and waste. We work with a dozen leading energy companies in Europe and North America, often helping them save millions of dollars a year while reducing their carbon emissions. 

We are committed to creating a culture in which people can be themselves and we strongly believe in building a diverse, equitable, and inclusive team. Myst offers a competitive salary, stock options, and benefits. In addition, we provide new hires the ability to choose between different risk/reward trade offs (i.e. combinations of stock and salary).