Researcher II - Data Scientist

NLR is seeking a skilled and versatile Data Engineer/Data Scientist to join our Data Engineering Group. This role will help to design, build, and maintain scalable and robust data pipelines analytical workflows, and computational tools that support data-driven research across the laboratory. You will also contribute to statistical modeling, exploratory data analysis, machine learning workflows, and reproducible research methods that enable scientific insight and decision-support for energy systems analysis.. The Data Engineering team is a multi-disciplinary team of data and software engineers, data scientists, and product developers that are at the forefront of developing advanced data solutions for strategic energy analysis at scale. Our work is focused on making energy data and software more accessible, usable, and actionable for researchers and engineers at NLR and beyond., Level II: Researchers at this level perform research independently, troubleshoot and execute complex technical tasks across multiple projects, and contribute to research products, working directly with more senior researchers. They review literature, interpret data within the context of the broader research community, and begin presenting findings to internal and external stakeholders.

Depending on project assigned, responsibilities may include:

Data Engineering & Architecture

• Design, construct, test, and maintain scalable data architectures, data lakes, databases, and datasets.

• Implement secure and compliant data models, ETL and analytical pipelines in a distributed and/or hybrid computing environment.

• Develop high-quality software solutions to manage data workflow, optimization, and retrieval.

• Implement secure and compliant data models and data governance practices in hybrid (on-prem/cloud/HPC) environments.

• Ensure data quality, integrity, and reproducibility across analytical workflows.

Data Science & Analytics

• Conduct exploratory data analysis, statistical modeling, and uncertainty/sensitivity analysis.

• Develop and apply predictive models, machine learning algorithms, and data-driven analytical methods.

• Support the development of generalizable, scalable physical system models for LCA, TEA, and other analytical frameworks.

• Explore and prototype the use of large language models and advanced analytics to enhance energy systems research.

• Visualize analytical results and communicate insights to technical and non-technical audiences.

Collaboration & Research Support

• Work closely with data engineers, data scientists, analysts, and subject matter experts to improve data collection, processing, and modeling methods.

• Contribute to research products including reports, publications, presentations, and software tools.

• Support concept paper and proposal development by providing data, analysis, and technical input.

• Develop documentation of data, software, processes, and procedures.

• Stay current with emerging tools, technologies, and best practices in data engineering and data science.

Our Team

You will join a team where everyone is striving to improve their knowledge of software development best-practices, while caring about creating the best possible solution to cutting edge problems. Our team creates secure, reusable, and efficient code, while supporting a variety of teams:

• A dynamic, interdisciplinary research and development environment at a leading national laboratory.

• Opportunities to collaborate with a diverse group of experts in software, data, and engineering domains.

• Work developing cutting-edge projects and contributing to research in the energy innovation industry.

For this position, we are looking for a candidate with experience working with some or all of: life cycle assessment, statistical techniques, model framework development, sensitivity and uncertainty analysis, and energy policy. The successful candidate must be able to operate within a large team of analysts and be responsive to quick turnaround requests and handle shifting priorities and project uncertainty. Additionally, the most successful candidates will have had demonstrated experience working with IRA and tax credits in analysis projects., Relevant Master's Degree . Or, relevant Bachelor's Degree and 2 or more years of experience . General knowledge and application of scientific technical standards, principles, theories, concepts and techniques. Training in team, task or project leadership responsibilities. Intermediate abilities and knowledge of practices and techniques. Beginning experience in project management. Good technical writing, interpersonal and communication skills.

• Must meet educational requirements prior to employment start date., * Familiarity with data engineering technologies (e.g., Python, SQL, ETL processes)

• Strong experience developing software and analyzing data with Python.

• Ability to translate technical requirements into structured data configurations.

• Strong understanding of data management concepts, data quality, and data cleaning.

• Experience with a diversity of data technologies and a curiosity to learn more.

• Strong analytical and problem-solving skills.

• Excellent interpersonal skills for engaging with both technical and non-technical users.

• Strong written and verbal communication skills for documenting workflows and explaining technical concepts.

• Ability to collaborate effectively in a team setting to meet project objectives., The ideal candidate will have a strong blend of both data engineering and software engineering skills with the ability to work on hybrid tech stacks. Cross-cutting, multi-disciplined candidates will be preferred as we are looking for an engineer who can be a "data-do-all" that can implement high quality, production ready code to solve a variety of research and big data problems.

Strong candidates will have many of the following expertise:

• Prior experience in the energy sector or a research environment is a plus.

• Experience and familiarity with lifecycle assessment modeling, technoeconomic modeling, and energy systems analysis.

• Excellent data visualization approaches and the ability to communicate complex analytical results to a diverse audience.

• Experience with big data (tens to hundreds of TB)

• Experience with version control (git/GitHub)

• Basic understanding of data management practices, such as multi-source data collection, workflow management, data storage, security, and availability, data governance & privacy.

• Familiarity with agile development

• Software and/or data quality assurance (verification and validation, testing, etc.)

• Experience with big data tools (e.g., Hadoop, Spark, Kafka, etc.), data pipelines, and software development frameworks

• Experience with parallel programming (High Performance Computing experience is a plus) and hybrid computing (on prem and in the cloud)

• Familiarity with cloud services (such as AWS S3/Glue/Athena/Lambda, Azure Blob Storage, GCP Storage/BigQuery), data warehousing solutions, and containerization technologies (Docker, Kubernetes).

• Experience with SQL, relational databases, and NoSQL databases.

• Knowledge of machine learning frameworks, statistical analysis, and algorithm optimization.

• Experience working with meteorological data (e.g., wind or solar data in NetCDF of HDF5 format). And cloud-friendly formats, like Parquet.

• Excellent analytical, problem-solving, and troubleshooting skills.

• Strong communication skills and the ability to collaborate effectively in a multi-project environment with a multidisciplinary team.

• Web and API development experience is a bonus.

• Familiarity with statistical modeling, Bayesian methods, and uncertainty quantification.

Benefits include medical, dental, and vision insurance; short*- and long-term disability insurance; pension benefits*; 403(b) Employee Savings Plan with employer match*; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; paid holidays; and tuition reimbursement*. NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Limited-term positions are not eligible for long-term disability or tuition reimbursement.

NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development. Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth. At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being., E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.