Community Energy Labs

Senior Data Scientist

Junte-se à Community Energy Labs como Senior Data Scientist nos EUA. Lidera soluções analíticas e de ML para otimizar o uso de energia em edifícios, ajudando a economizar dinheiro e reduzir emissões. Trabalho remoto, salário competitivo e projetos com impacto em energia limpa.
Community Energy Labs
Community Energy Labs
Estados Unidos Remoto Tempo inteiro 155 000–185 000 US$ por ano UTC-08:00

Community Energy Labs

Visão Geral da Empresa

Nome

Community Energy Labs, uma empresa de tecnologia energética com fins lucrativos, liderada e de propriedade feminina

Sede

Portland, Oregon, Estados Unidos

Fundação

2020

Tamanho

Menos de 10 funcionários (fonte: techjobsforgood.com)

O Que Fazem

A Community Energy Labs é especializada em gerenciamento e controle de energia predial, com foco em viabilizar de forma acessível as metas de descarbonização de edifícios comunitários até 2030 (fonte: greentownlabs.com). Seu produto principal é uma plataforma de controle IoT e Software como Serviço, projetada para operadores de edifícios que enfrentam metas e tarifas energéticas complexas e onerosas (fonte: communityenergylabs.com). O sistema instala sensores sem fio e controladores de equipamentos, utilizando software baseado em nuvem alimentado por controle preditivo de modelo e aprendizado de máquina para prever e otimizar autonomamente a operação dos equipamentos prediais, maximizando a energia proveniente de fontes limpas e acessíveis (fonte: greentownlabs.com). Suas soluções monitoram, aprendem e ajustam o uso de energia do edifício para atingir as metas dos clientes, controlando pontos de ajuste, horários, qualidade do ar, conforto e consumo energético (fonte: forclimatetech.org). Voltada para proprietários e operadores de edifícios comerciais e comunitários, a plataforma reduz o esforço para cumprir metas energéticas por meio da automação e menores custos iniciais, possibilitando retorno do investimento em meses, e não anos (fonte: forclimatetech.org).

Projetos e Histórico

A Community Energy Labs construiu um sólido histórico de validação e reconhecimento por meio de diversos prêmios prestigiados e programas de aceleração, em vez de grandes projetos com concessionárias. Sua plataforma de controle de edifícios limpos com IA foi vencedora regional do acelerador internacional CleanTech Open 2020 e vencedora geral do desafio Go Vertical 2020 da Madrona Venture Labs (fonte: greentownlabs.com). Também foram reconhecidos como inovadores de edifícios impel+ em 2021, membros da coorte EPRI Incubate Energy 2021, premiados pelo SBIR do Departamento de Energia dos EUA em 2021 e receberam o voucher CalTestBed da Comissão de Energia da Califórnia em 2021 (fonte: greentownlabs.com). Além disso, a Community Energy Labs promoveu workshops de resiliência para ajudar comunidades a entender o uso de energia em edifícios e melhorar sua resiliência (fonte: communityenergylabs.com).

Desenvolvimentos Recentes

Nos últimos dois anos, a Community Energy Labs concentrou-se em expandir sua equipe e fortalecer sua presença pública por meio de recrutamento ativo, em vez de grandes aquisições ou anúncios de financiamento. Sua página de carreiras lista vagas abertas, incluindo Engenheiro de Software Sênior e Engenheiro de Suporte Técnico, com a posição de engenheiro de software sênior oferecendo faixa salarial entre US$ 135.000 e US$ 165.000 (fonte: communityenergylabs.com, techjobsforgood.com). A empresa mantém afiliações no ecossistema, como a associação à Greentown Labs e reconhecimento pela For ClimateTech, apoiando sua visibilidade no setor de tecnologia para edifícios limpos (fonte: greentownlabs.com, forclimatetech.org).

Trabalhar Lá

A Community Energy Labs contrata principalmente para cargos de engenharia de software e suporte técnico diretamente ligados à sua plataforma de controle predial, com vagas documentadas para Engenheiro de Software Sênior e Engenheiro de Suporte Técnico (fonte: communityenergylabs.com). A empresa é liderada pela fundadora, com a CEO Tanya Barham trazendo duas décadas de experiência como inovadora, empreendedora, tecnóloga e especialista em concessionárias, fomentando uma cultura de startup focada na descarbonização prática de edifícios e otimização energética (fonte: communityenergylabs.com). O ambiente de trabalho enfatiza o desenvolvimento de produtos e a implementação para clientes, em vez de construção ou financiamento de grandes projetos, apoiando uma abordagem orientada por missão para gestão inteligente de energia acessível (fonte: forclimatetech.org).


Última atualização em mai 19, 2026 | Relatar um problema

The Senior Data Scientist role contributes to Community Energy Labs by leading analytics solutions, designing ML architectures, collaborating with teams, and optimizing models for business outcomes needed to help our customers reach their goals, whether that's saving money or saving the planet.

What We Do

Community Energy Labs (CEL) develops AI-powered control systems that help buildings interact with the grid and use energy when it's clean, cheap, and abundant - and less when it's not. We currently focus on schools and community buildings, which make up nearly 30% of U.S. commercial floorspace and often lack the staff or budgets to manage energy effectively.

Our platform combines machine learning and advanced control algorithms to automate HVAC and building energy management, optimizing for cost, comfort, and carbon reduction. We're now evolving from prototype to scalable product - including building a new, modern user interface from the ground up - to scale clean-energy intelligence from tens to hundreds of real-world sites.

CEL's work has been recognized by the U.S. Department of Energy, NSF, USDA, California Energy Commission and programs like Elemental Impact and Google for Startups. If you're a collaborative pragmatic, and business-savvy technical leader this is where your work matters.

Essential Functions & Responsibilities

Role Summary

  • Lead cross-functional teams to define, build, validate and deploy advanced predictive analytics solutions that drive measurable business outcomes.
  • Translate business objectives and stakeholder needs into clear analytical requirements
  • Design and vet appropriate methods, algorithms, data preparation and feature engineering plans to share with product engineering and non-technical stakeholders.
  • Work collaboratively to build engineering requirements and provide input to products that forecast, optimize, and act across building energy systems in the real world.
  • Audit, simplify and productize existing Jupyter notebooks and production data science systems. Align code behavior, model assumptions and derived signals with CEL's Common Information Model, business workflows, and real-world building operations.

Expected Hours of Work and Travel

  • This is an exempt position.
  • This position is at-will.
  • This position is a full time position that may occasionally require extra hours and weekend work that is not compensated as overtime.
  • This position is remote and open to United States based candidates.
  • Standard work is generally Monday through Friday during core business hours (8:30am - 5:30 pm Pacific time)
  • Occasional travel may be required for customer deployments, team meetings.

Supervisory Responsibilities

  • This is a senior individual contributor role that has no supervisory responsibility over any employees; however, you will collaborate heavily with a very small team of non-technical, technical engineering and national lab staff so you must be a direct, strong communicator and effective at planning, communicating and documenting.

Physical Requirements

  • Prolonged periods of computer work.
  • Ability to communicate by video, phone, email, and chat.

Salary

  • Base salary range: $155,000-$185,000, with milestone-based incentive compensation tied to agreed product, deployment, and platform outcomes.
  • As a start-up organization, each employee's salary is dependent on grants and other funding secured by CEL.

Essential Functions: Senior Data Scientist

Translate Business Objectives

  • Lead cross-functional work with Product, Engineering, Operations, Customer Success, National Lab partners and company leadership to articulate data science and analytics priorities.
  • Translate business, customer, utility, and product needs into clear analytical requirements, success metrics, and implementation plans.
  • Evaluate near, medium and long-term tradeoffs between analytical rigor, engineering effort, product value, customer impact, and deployment risk. Break down and estimate work.
  • Communicate findings, assumptions, risks, and recommendations clearly to technical and non-technical stakeholders through established company artifacts and cadences.
  • Synthesize large-scale, disparate datasets - including metadata, meter data, device telemetry, settlement data, and logs - to aid in increasing the impact of our products and services.

Design & Optimize Solutions to Real-World Problems

  • Partner with business operations, engineers to define problem statements, success metrics, and deployment requirements.
  • Design and deploy constrained optimization systems for real-world operations (MPC, LP, MILP) that are aligned with stakeholder and business outcomes.
  • Develop forecasting systems and integrate them into optimization pipelines, e.g. deep learning models (LSTM, RNN, probabilistic models).
  • Design and implement robust data ingestion, storage, integration, processing, retrieval, and management strategies for relevant datasets. Call out potential risks early and propose mitigation plans.
  • Apply appropriate statistical, machine learning, optimization, and control methods to the following use cases: energy demand, HVAC load, weather, occupant comfort, energy cost, energy use (kWh) and peak demand (kW).
  • Support decision systems that act predictably across building and grid conditions - even with flaky iot devices and overwhelmed human operators in the loop.
  • Produce crisp exhibits and memos that explain methods, limitations, and uncertainty.

Build Stable Product & Lead Through Example

  • Lead the design and implementation of scalable, robust, and high-performance ML architectures including MLOps, AIOps leveraging cloud native services (AWS).
  • Partner with software and data engineers to translate analytical methods into reliable production services and workflows. Document your work.
  • Build transparent, reproducible pipelines and analysis environments in cloud infrastructures.
  • Improve accuracy, reliability, cost, scalability, and maintainability.
  • Help CEL make better decisions - perform code reviews, support your peers, and coach and listen to junior and non-technical members.

Qualifications

Required Experience

  • Advanced degree or equivalent experience in Applied Mathematics, Physics, Mechanical Engineering, Electrical Engineering, Controls, Operations Research, Computer Science, or a related quantitative field.
  • 5+ years of experience building production-grade models, optimization systems, forecasting systems, or control systems.
  • 5+ years of experience with data engineering and data pipelines.
  • 5+ years of experience with software programming/scripting (such as Python and scientific computing tools such as NumPy, pandas, SciPy, TensorFlow, PyTorch, or similar tools; Unix/Linux type batch scripting; SQL; C / C++) c.
  • Experience taking over legacy or research-quality analytical systems and creating a practical path toward tested, simplified, maintainable production code.

Necessary Skills/Abilities

  • Ability to work through ambiguity, excellent problem solving skills and attention to detail.
  • A bias toward clarity, simplicity, and defensibility over black-box modeling are essential.
  • Experience designing end-to-end systems and not just isolated components.
  • Strong judgment about when to preserve, refactor, centralize, replace or stop existing work.
  • Clear written and verbal communication with technical and non-technical audiences. In particular, ability to create math-to-code mappings, as-built documentation, validation plans and implementable engineering requirements.
  • 3+ years of experience in one or more of: constrained optimization (LP, MILP, MPC), ML / time-series forecasting, control systems, applied mathematics.
  • Software best practices, including testing, clean code, version control, and debugging.
  • Exposure to and familiarity with cloud platforms, containerized applications, SQL/time-series databases, FastAPI, Redis, MQTT, and MLOps.

Nice to Have but Not Required

  • Experience with energy systems, grid operations, DER coordination, demand response, HVAC, smart devices, building thermal dynamics, or building controls.
  • Experience applying physics-informed or first-principles modeling to real-world systems.

Attributes

Ideal CEL community members demonstrate

  • Curiosity
  • Entrepreneurial drive
  • High accountability
  • Attention to detail
  • A pragmatic approach to effort vs. value
  • Empathy for customers & team
  • Transparency
  • Willingness to communicate & teach

Yes, That Means You!

We've read the research and we know that certain underrepresented groups in tech might read our post and think "Oh, gee, well I only have nine out of ten qualifications." If our mission and this job speak to you and you have the interest and ability to work smart, learn, and grow with us then we want you to apply for this job!

Community Energy Labs is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by state or federal law.

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Sobre a função

6 agosto 2026

13 agosto 2026

Tempo inteiro

Remoto

Empresa

155 000–185 000 US$ por ano

Redes inteligentes

Community Energy Labs

communityenergylabs.com

  •  Estados Unidos

5+ years of experience

UTC-08:00