Senior Data Scientist, Special Projects

Location: Remote,None,None

Accepting applications until April 10 at 5pm E.T.

About WattTime

WattTime is a nonprofit tech start-up. We find or conduct original research into emissions datasets that can unlock new or more effective emissions-reducing interventions, then help implement and scale those interventions. Our best known intervention is Automated Emissions Reduction (AER), the technique currently used by over 1 billion devices daily (e.g. all Nest thermostats, U.S. iPhones, Toyota EVs, etc) to cut their carbon footprints by using energy when the grid has surplus clean energy. We also enabled and scaled other techniques, like Emissionality, a technique to multiply the emissions benefits of renewable energy.

WattTime is also the secretariat of Climate TRACE, a joint initiative of over 100 non-profits, tech companies, universities, and individual researchers pooling their expertise in AI, remote sensing, and emissions data to collectively build a highly advanced comprehensive open global greenhouse gas measurement system. Climate TRACE is a powerful enabler of novel emissions-reducing interventions, as well as an important transparency tool in its own right.

About the Role

The world of emissions data is speeding up. Between AI-based vibe coding and the tremendous consolidation happening in emissions datasets, it’s becoming more and more common that entirely new concepts for how to monitor or use emissions data to drive impact can sometimes be prototyped in as little as a day. And given WattTime’s growing prominence supporting hundreds of the world’s premiere emissions organizations, we are getting asked for possibly important new features almost daily. So we have a growing need for people who can operate in a world where it’s ever faster to develop new interventions, yet more important than ever to triage.

The role of Senior Data Scientist, Special Projects will have elements of a data scientist, product manager, and quantitative marginal gains expert. Your role will not be to dream up new possible projects (we have plenty). It will be to jump in on many new potential projects already under consideration. To rapidly prototype, apply critical thinking and decision science to triage which projects are likely to most increase our impact per day, and swiftly either prove out or ruthlessly deprioritize projects.

All of this will be possible at speed because you’ll be drawing on WattTime’s vast related capabilities, from our unparalleled and highly structured emissions data, to remote sensing resources, to our deep network of users. Unlike most roles at WattTime, your work will be cross-cutting across multiple teams. But you’ll have to stay focused and resist going down rabbit holes.

A successful applicant for this role will demonstrate they can think not in terms of success or failure, but in terms of how to maximize impact per day. To do this, you will need to rapidly understand complex novel emissions data concepts; grab large amounts of data in ETL pipelines that do not necessarily need to be reusable; rapidly build good-enough prototypes; quantify impacts if projects succeed; analyze systems for marginal additional impact from improving various limiting factors (engineering, economic, and political); iteratively chip away at those limitations; and communicating all the above in plain English. 

Responsibilities

• First-order modeling: Rapidly stitch together estimates of relevant variables from data you can rapidly obtain (e.g. health harm caused by different Climate TRACE assets)

• Data assimilation: Iteratively improve estimates by continuously improving algorithms with new input data using Bayesian updating or similar methods

• Construct ETL pipelines: Pull, clean, format, and organize relevant data from the web, satellites, our databases, and partners

• Technical communication: Write clear methodologies, API documentation, and papers for technical audiences

• Stakeholder communication: Write brief punchlines or blog posts for team members, policymakers, nonprofits, and corporate decision makers

• Comparative causal inference analysis

• Estimate the causal impact of various interventions (like building solar)

• Quantify opportunities to increase impact