Machine Learning Engineer / Data Scientist - Climate and Energy Policy

About Planet Reimagined Planet Reimagined uses an innovative action-research method to incubate and scale creative solutions to our most pressing climate problems. With an unwavering focus on impact, we bring researchers and advocates from around the world to collaborate on initiatives that touch all aspects of the climate crisis: energy, waste, water, farming, finance, production, transportation, environmental justice and so much more. Our action-research method trains and engages the climate leaders of the future while using media and entertainment platforms to reinforce strategic advocacy to mobilize climate action.

Planet Reimagined

Creating engagement around sustainability through media, research, and incentive based initiatives

MediaCampaignsInequalityEnvironmentalismPodcastand Advertising

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planetreimagined.com

11-50 employees

Non-profit Organizations

New York City

Nonprofit

5.1k LinkedIn followers

• Planet Reimagined is seeking a Machine Learning Engineer / Data Scientist to
• design and build cutting-edge data systems that accelerate climate solutions
• across local and federal scales. Join our mission-driven team building one of
• the world's first ML systems for hyper-local policy analysis and
• recommendations. You'll design, train, and deploy models, and build the
• knowledge graphs, wikis, and other structured datasets behind them, to identify
• successful climate interventions, predict how they adapt to new contexts, and
• optimize renewable energy deployment from city councils to federal land
• management.
• Founded by a multi-platinum musician and a UN advocate, Planet Reimagined was
• built on the belief that big change happens when people act together and when
• that action drives shifts in policy and industry. On a mission to deliver fair
• solutions for people and the planet, we use an innovative action research method
• to incubate and scale creative solutions to our most pressing climate problems.
• We mobilize fans at concerts to take real-time civic action, and we help
• renewable energy companies access public lands once closed to them. From
• legislative wins to global campaigns, we turn bold ideas into action. And we’re
• just getting started.
• Build LLM-powered knowledge graphs, wikis, and other structured datasets from
• policy documents, municipal records, community sentiment, and federal energy
• data, along with the human-readable layers rendered from them.
• Develop LLM and NLP pipelines that extract policy elements, resolve entities,
• and link them across sources
• Track data provenance so every policy element traces back to its source
• document, passage, and extraction method
• Design human-in-the-loop workflows where policy experts validate extracted
• policy elements, and their corrections improve the models, scripts, and
• prompts
• Construct policy timelines by extracting and ordering events to show how
• climate solutions unfold over time
• Design, train, and deploy models for policy effectiveness scoring, solution
• replicability, and energy development potential
• Build recommendation and graph-based models that match proven climate
• policies to a specific city, county, or community
• Own the full modeling lifecycle: baselines, feature engineering, model
• selection, tuning, and error analysis
• Develop evaluation frameworks to measure model, extraction, and LLM output
• quality against expert-validated ground truth
• Analyse community-stentiment data to quantify support for climate policies
• within surveyed localities
• Build systems to facilitate rigorous comparative analysis, helping policy
• experts map when, where, and how policies succeed and identify causal
• dynamics that may transfer to other contexts.
• Analyze policy timelines to measure adoption lags, implementation speed, and
• time to impact
• Perform exploratory analysis and predictive modeling to find patterns in
• climate solution adoption and renewable energy development opportunities
• Communicate findings through visualizations and automated reporting for
• climate and energy transition planning
• Deliver insights from the analysis of interaction and call-to-action
• conversion data to improve in-concert advocacy efforts
• experiment tracking, versioning, and a model registry
• Automate CI/CD for models, with validation gates and staged rollouts
• Maintain the data pipelines and API integrations (BigQuery, Cloud Functions)
• that feed models from government, community, and federal data sources
• Monitor model performance, data drift, and knowledge graph quality, with data
• governance for sensitive municipal data and PII.

Required

• 3-5 years of experience in data science and ML engineering, preferably in
• GCP/AWS/Azure ecosystem
• Strong proficiency in LLM application design, context engineering strategies,
• Hands-on experience building functional knowledge systems for LLM
• applications
• Proven ability to work with varied, unstructured data sources including
• municipal records and reports, news coverage, video documentation, and
• government datasets.
• Strong problem-solving skills and ability to thrive in ambiguous climate
• policy and energy environments
• Excellent communication skills for cross-functional collaboration with policy
• experts, community stakeholders, and federal planners including turning data
• analysis into data storytelling outputs.
• Data Tools: Pandas, NumPy, dbt, Apache Beam/Dataflow
• API Development: REST APIs, government data integrations, real-time community
• sentiment and federal climate data augmentation
• Infrastructure: Cloud Functions, Pub/Sub, Cloud Run, CI/CD with Cloud Build
• Databases: BigQuery (primary), Firestore, vector databases (Vertex AI Vector

Preferred

• Background or strong interest in climate policy, municipal governance,
• federal land management, or energy transition planning
• Experience with government data sources, regulatory documents, federal
• climate records, and civic data standards
• Knowledge of policy analysis frameworks, community engagement measurement,
• and renewable energy development processes
• Previous work in mission-driven organizations focused on local government,
• federal policy, or climate action
• You're a curious, adaptable engineer who gets energized by complex problems
• without clear solutions. You enjoy building systems from scratch, can navigate
• policy ambiguity with confidence, and are motivated by the potential to create
• tools that help communities and governments replicate successful climate
• solutions while optimizing renewable energy deployment. You balance technical
• excellence with practical climate impact, and you're excited to work at the
• intersection of data science, community-driven climate action, and federal
• energy policy.
• Ready to help accelerate America's climate progress through data-driven policy
• solutions? We'd love to hear from you.

• The salary range for this position is $120,000 – 150,000.
• The final offer will consider factors like the candidate’s location, cost of
• living, and experience level.
• We take a location-aware approach to compensation to ensure fairness and
• competitiveness across markets. For example, within the U.S., this range aligns
• with typical salaries for similar roles in major markets such as New York or
• Seattle (generally $140,000–$150,000) and mid-cost regions such as Dallas or
• Charlotte (typically $120,000–$130,000).
• U.S.-based full-time employees are eligible for a comprehensive benefits
• package, including healthcare, dental, and vision coverage, retirement plans,
• and paid time off. Additional benefits include a remote but highly collegial
• working environment.
• Ability to pass a background check.
• U.S. Citizenship or U.S. work authorization
• Ability to provide 3 professional references including a recent supervisor
• Take home assessment
• One-on-one session with hiring manager to review your work
• Panel Interview with our team for you to present your work