Data Scientist III - Building Energy Applications

Pacific Northwest National Laboratory; Seattle (WA); On-site; USD 140,000 - 229,000; Full time

Benefits offered by this job

Health insurance

Retirement benefits

Job summary

Pacific Northwest National Laboratory in Seattle, WA, seeks a Data Scientist III - Building Energy Applications to lead AI and data science work applied to building energy performance. The role requires strong programming and data analysis skills and experience in AI/ML methods, with responsibility for guiding technical work and collaborations.

This position is based at a PNNL office in Seattle, with an on-site presence expected.

Qualifications

• Advanced experience developing and evaluating AI or machine learning models for scientific or engineering applications.
• Ability to lead technical tasks and projects with independence and judgment.
• Experience organizing and integrating datasets from multiple sources for analysis.
• Experience with building energy codes or permitting processes is a plus.

Responsibilities

• Lead data science and AI research applying methods to building energy performance.
• Develop reusable tools and reproducible data workflows for research.
• Create and maintain visualizations, dashboards, and infographics.
• Mentor junior staff and review analytical work and code.
• Collaborate with sponsors and stakeholders to translate needs into methods.

Skills

Programming

Data analysis

AI/ML models

Technical leadership

Python

Education

BS/BA

MS/MA

PhD

Tools

Tableau

SQL

Data pipelines

Version control

Job description

Overview

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.

Our Science & Technology directorates include National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment.

In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus.

The Energy and Environment Directorate delivers science and technology solutions for the nation’s biggest energy and environmental challenges. Our more than 1,700 staff support the Department of Energy (DOE), delivering on key DOE mission areas including: modernizing our nation’s power grid to maintain a reliable, affordable, secure, and resilient electricity delivery infrastructure; research, development, validation, and effective utilization of renewable energy and efficiency technologies that improve the affordability, reliability, resiliency, and security of the American energy system; and resolving complex issues in nuclear science, energy, and environmental management.

The Electricity Infrastructure and Buildings Division, part of the Energy and Environment Directorate, is accelerating the transition to an efficient, resilient, and secure energy system through basic and applied research. We leverage a strong technical foundation in power and energy systems and advanced data analytics to drive innovation, transform markets, and shape energy policy.

Responsibilities

This position is in the Building Simulation and Design Group (BS&DG) within PNNL’s Electricity Infrastructure and Buildings Division. BS&DG conducts modeling and analysis to evaluate the impacts of building energy policies, codes, and standards; develops tools and workflows to support building research and decision making; and helps accelerate adoption of energy-efficient technologies. The group maintains core research capabilities in building energy simulation, building energy policy analysis, and tool development for building applications.

The BS&DG is seeking a Data Scientist III - Building Energy Applications with strong programming and data analysis skills, advanced expertise in artificial intelligence and machine learning, and demonstrated ability to lead technical work. The selected candidate will serve as a hands‑on technical lead. They will select and develop technical approaches and lead research applying data science and AI methods to building energy performance, building technologies, equipment, and energy efficiency policies, codes, and standards. Responsibilities include developing and improving analytical tools and reproducible data workflows, creating and maintaining data visualizations and infographics, guiding technical contributors, ensuring the technical quality of research results, and communicating findings to sponsors and stakeholders. The candidate will also develop and evaluate AI‑enabled methods and tools for permitting modernization, predictive modeling, building‑system controls, and research workflow automation, with an emphasis on accuracy, reproducibility, and practical value.

This position is based at a PNNL office in Seattle, WA, with an on‑site presence expected. Hybrid work arrangements may be available in accordance with laboratory policy, project needs, and team expectations.

The successful candidate will be responsible for:

• Performing assigned roles under the direction of Project and/or Task Managers, following applicable project and field procedures, and completing assigned tasks on time and within budget.
• Defining research questions and selecting and developing data science and AI approaches to address building energy performance, technology, and codes and standards challenges, including appropriate methods, assumptions, evaluation metrics, and study boundaries.
• Organizing, integrating, and analyzing building and equipment datasets from field studies, operational measurements, surveys, product information, simulation results, and permitting and code-related documents.
• Designing and leading analytical studies to evaluate building technologies, equipment, energy efficiency policies, codes, and standards, including selecting appropriate baselines, comparing performance and energy use, and conducting sensitivity, scenario, and uncertainty analyses as appropriate.
• Developing, training, and evaluating statistical and machine learning models for building and equipment performance prediction, system identification, anomaly detection, and building‑system controls, incorporating engineering knowledge and constraints in collaboration with relevant specialists.
• Developing and evaluating AI‑enabled tools for permitting modernization and research workflow automation, including methods for extracting, organizing, and analyzing information from technical documents and supporting review processes.
• Developing reusable tools and improving reproducible workflows for data preparation, integration, quality checks, analysis, and reporting, including maintaining organized research datasets and collaborating with database and software developers.
• Establishing data validation and model‑evaluation procedures, investigating data quality issues and unexpected findings, and assessing accuracy, robustness, analytical consistency, and reproducibility using appropriate benchmarks, reference data, statistical methods, and engineering knowledge.
• Creating and maintaining clear visualizations and updating the data underlying dashboards, infographics, and other research products.
• Leading major technical tasks or moderate projects, coordinating contributors, and managing assigned scope, schedule, budget, technical quality, and deliverables while remaining directly involved in programming, analysis, and method development.
• Working with sponsors, collaborators, and stakeholders to understand research needs, translate those needs into technical approaches, and communicate progress, findings, and limitations.
• Mentoring junior staff and reviewing analytical methods, models, code, and technical products developed by team members.
• Leading the development of technical reports, journal articles, and conference presentations, and representing project work in sponsor meetings and technical forums.
• Generating research ideas, developing funding opportunities with project teams, and leading technical sections of proposals.
• Collaborating across the group and division to share methods, strengthen research capabilities, and identify opportunities for related research.
• Maintaining accountability to Project and/or Task Managers, the Group Leader, and the Team Leader for assigned responsibilities, project execution, professional development, and operational discipline, including compliance with applicable procedures, training requirements, and quality, safety, and security expectations.

Qualifications

Minimum Qualifications:

• BS/BA and 5+ years of relevant work experience -OR-
• MS/MA and 3+ years of relevant work experience -OR-
• PhD with 1+ year of relevant experience

Relevant experience includes: graduate degree in data science, computer science, statistics, applied mathematics, electrical engineering, or a closely related field; strong programming and data analysis skills; advanced experience developing and evaluating AI or machine learning models for scientific or engineering applications; and experience independently developing technical approaches and leading technical tasks?

Preferred Qualifications:

• Graduate degree in data science, computer science, statistics, applied mathematics, electrical engineering, or a closely related field, with at least four years of relevant experience and demonstrated technical leadership and independent judgment in applied research.
• Strong programming and data analysis skills using Python or comparable tools, with experience developing reusable software and reproducible workflows for data preparation, quality assurance, analysis, and reporting.
• Advanced experience developing, training, and evaluating machine learning models for scientific or engineering applications, including selecting methods, establishing baselines and evaluation metrics, assessing uncertainty and limitations, and validating results.
• Experience incorporating physical relationships, engineering knowledge, or operational constraints into data‑driven models, predictive methods, or optimization approaches for energy systems or related engineering applications.
• Experience developing and evaluating tools using large language models or other generative AI methods for technical information analysis, decision support, or research workflow automation. Experience applying these methods to permitting or code‑related processes is a plus.
• Experience organizing and integrating datasets from multiple sources, investigating data quality issues, applying appropriate statistical methods, and developing defensible interpretations of results.
• Experience analyzing energy systems, building equipment, or related engineering systems in collaboration with domain specialists. Familiarity with building energy codes, equipment standards, or permitting processes is a plus.
• Experience creating and maintaining clear data visualizations and analytical interfaces, including dashboards, infographics, or other products that communicate complex findings. Familiarity with Tableau or comparable tools is a plus.
• Experience with version control, testing, documentation, and collaborative software development for research tools and analytical workflows. Experience with SQL, data pipelines, or scalable computing is preferred.
• Demonstrated experience selecting and developing technical approaches, leading technical tasks or projects, coordinating contributors, and delivering technically sound results within assigned scope, schedule, and budget while remaining directly involved in programming and analysis.
• Experience mentoring technical contributors and reviewing analytical methods, models, code, or research products developed by others.
• Strong written and verbal communication skills, with experience developing technical reports, publications, presentations, or research software; contributing technical content to proposals; and communicating effectively with sponsors, collaborators, and interdisciplinary teams.

Hazardous Working Conditions/Environment

Not Applicable

Testing Designated Position

This is not a Testing Designated Position (TDP).

About PNNL

Pacific Northwest National Laboratory (PNNL) is a world‑class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!

At PNNL, you will find an exciting research environment and excellent benefits including health insurance, and flexible work schedules. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab’s campus is only a 45-minute flight (or ~3 hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.

Commitment to Excellence and Equal Employment Opportunity

Our laboratory is committed to fostering a work environment where all individuals are treated with fairness and respect while solving critical challenges in fundamental sciences, national security, and energy resiliency. We are an Equal Employment Opportunity employer.

Pacific Northwest National Laboratory (PNNL) is an Equal Opportunity Employer. PNNL considers all applicants for employment without regard to race, religion, color, sex, national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws.

We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at [e-mail].

Drug Free Workplace

PNNL is committed to a drug‑free workplace supported by Workplace Substance Abuse Program (WSAP) and complies with federal laws prohibiting the possession and use of illegal drugs.

If you are offered employment at PNNL, you must pass a drug test prior to commencing employment. PNNL complies with federal law regarding illegal drug use. Under federal law, marijuana remains an illegal drug. If you test positive for any illegal controlled substance, including marijuana, your offer of employment will be withdrawn.

Security, Credentialing, and Eligibility Requirements

As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.

For foreign national candidates:

If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.

Mandatory Requirements

Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.

Rockstar Rewards

• Employees and families are offered medical insurance, dental insurance, vision insurance, robust telehealth care options, several mental health benefits, free wellness coaching, health savings account, flexible spending accounts, basic life insurance, disability insurance*, employee assistance program, business travel insurance, tuition assistance, relocation, backup childcare, legal benefits, supplemental parental bonding leave, surrogacy and adoption assistance, and fertility support. Employees are automatically enrolled in our company‑funded pension plan* and may enroll in our 401 (k) savings plan with company match*. Employees may accrue up to 120 vacation hours per year and may receive ten paid holidays per year.
• * Research Associates excluded.
• **All benefits are dependent upon eligibility.

Notice to Applicants

PNNL lists the full pay range for the position in the job posting. Starting pay is calculated from the minimum of the pay range and actual placement in the range is determined based on an individual’s relevant job‑related skills, qualifications, and experience. This approach is applicable to all positions, with the exception of positions governed by collective bargaining agreements and certain limited‑term positions which have specific pay rules.

As part of our commitment to fair compensation practices, we do not ask for or consider current or past salaries in making compensation offers at hire. Instead, our compensation offers are determined by the specific requirements of the position, prevailing market trends, applicable collective bargaining agreements, pay equity for the position type, and individual qualifications and skills relevant to the performance of the position.

Minimum Salary

USD $140,200.00/Yr.

Maximum Salary

USD $228,800.00/Yr.