Full Stack Data Science Lead - Analytics & Machine Learning
WattBuy · Seattle, WA/Washington, DC/Remote (USA)
At WattBuy, we are focused on an ambitious vision: making cleaner, more affordable electricity accessible to every household. Our energy marketplace and platform provides actionable insights to millions of energy consumers by estimating their electricity usage, costs, and carbon footprint. We deliver these insights directly to consumers using WattBuy.com; through partnerships with leading enterprises in real estate, personal finance, and smart devices; and through self service APIs made available through a developer portal.
Wattbuy is a fully distributed team looking for passionate and mission-driven teammates across all time zones to help drive our next phase of growth. As a WattBuy Data Scientist, you’ll need to be conversant in all aspects of our product, making recommendations for future features or iterations based on trends in the data. You’ll also work on the machine learning models that power our electricity estimation product suite.
You should be able to improve existing machine learning models, and also be able to identify new opportunities and create valuable models using knowledge of the business needs and our access to various sources of data.
• Work closely with leadership to identify important questions and answer them with data
• Own the machine learning model for electricity estimation, create a backlog for future improvements
• Be a company-wide resource for all things data science, able to research and guide us on a topic if you don’t have existing expertise (NLP, computer vision, etc.)
• Create key customer metrics, tracking and visualizing them for senior leadership.
• Communicate analyses and data-backed recommendations to stakeholders
• Championing a data-first approach toward decision-making across the entire organization
• Time Series Forecasting
• Some industry experience in a Product Data Science role, or in a engineering role with some data science responsibilities
• Understanding of various statistical techniques and experimentation analysis workflows
• Data engineering experience and data pipeline tooling experience is a plus
• Bachelor's degree or equivalent work experience in Computer Science, Mathematics, Statistics, Operations Research, or a closely related field