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National Renewable Energy Laboratory Staff Scientist - Data Science in Golden, Colorado

Posting Title

Staff Scientist - Data Science

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Location

CO - Golden

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Position Type

Regular

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Hours Per Week

40

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Job Description

The Data, Analysis and Visualization Group in the NREL Computational Science Center has an opening for a full-time researcher in applied predictive modeling, data analysis, and visualization with an emphasis in machine learning techniques, streaming data analytics, and machine vision.

NREL Is looking for a dynamic, motivated researcher with a strong technical background and an interest in the mission of NREL. The successful candidate will collaborate with NREL staff and researchers, other national labs and universities on efforts to develop data science solutions at scale to real-world problems in renewable energy research. In addition to existing skills, candidates should demonstrate a high degree of curiosity, willingness to learn new skills and ability to adapt to the data needs of differing domains.

Specific projects relevant to this position include object recognition and image classification (e.g., YOLO), streaming data systems design and implementation (e.g., Kafka and Druid), performance analysis, transportation systems and automation. Applicants should have demonstrated research experience and a strong record of publication, as well as experience leading technical tasks.

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Basic Qualifications

PhD in Computer Science or related. Or, Master's Degree in Computer Science or related and 3 or more years of experience . Or, Bachelor's Degree and 5 or more years of experience .

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Additional Required Qualifications

Demonstrates complete understanding and wide application of scientific technical procedures, principles, theories and concepts in the field. General knowledge of other related disciplines. Demonstrates leadership in one or more areas of team, task or project lead responsibilities. Demonstrated experience in management of projects. Very good technical writing, interpersonal and communication skills.

Preferred Qualifications

Required: ​

  • Demonstrated experience with predictive modeling and classification using machine learning methods, neural networks, and open source frameworks.

  • Significant experience programming programming in Python on diverse applications.

  • Candidates should be able to demonstrate some existing skills and experience in applying data science in industry, academia, or government settings.

  • Familiarity with foundational statistical concepts such as regression models, uncertainty quantification, Bayesian analysis, model selection, clustering, outlier detection, etc.

  • Experience in big data analytics on diverse, asynchronous data sets including experience in designing efficient and robust ETL workflows.

  • Sufficient software engineering expertise to enable big data solutions: object-oriented design, coding and testing patterns; engineering software platforms and large-scale data infrastructures.

  • Experience using deep learning frameworks (e.g., TensorFlow) on high performance computing/GPU platforms.

  • Experience with parallel and distributed programming, big data frameworks, notably including streaming data systems (e.g., Kafka), and scientific plotting libraries (e.g., plot.ly, matplotlib).

  • A strong familiarity with Unix/Linux operating systems and open source software.

  • Background in relevant engineering disciplines esp. of transportation systems, vehicle technologies, and/or power systems.

  • Candidates should be able to demonstrate some existing skills and experience in applying data science in industry, academia, or government settings. Interested candidates should have experience programming Python and R (optionally, in addition to other languages), accessing APIs and databases (SQL), demonstrated experience with machine learning and applied predictive modeling, applied statistical analysis, as well as a high degree of curiosity, willingness to learn new skills and ability to adapt to the data needs of differing domains.

Preferred:

  • A strong familiarity with Unix/Linux operating systems and open source software. Preferably in a production data-center cloud or HPC environment.

  • Familiarity with foundational statistical concepts such as regression models, uncertainty quantification, Bayesian analysis, model selection, clustering, outlier detection, etc.

  • Experience in big data analytics on diverse, asynchronous data sets including experience in designing efficient and robust ETL workflows. Experience accessing and designing APIs and databases (SQL).

  • Sufficient software engineering expertise to enable production-quality solutions: object-oriented design, coding and testing patterns; engineering software platforms and large-scale data infrastructures. Interested candidates should have experience programming Python and R (optionally, in addition to other languages).

  • Experience using deep learning frameworks (e.g., TensorFlow) on high performance computing/GPU platforms.

  • Experience with parallel and distributed programming, big data frameworks, notably including streaming data systems (e.g., Kafka), and scientific plotting libraries (e.g., plot.ly, matplotlib, bokeh, ggplot).

  • Background in relevant engineering disciplines especially: vehicle technologies, power systems, grid, smart cities and campuses, IOT.

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Annual Salary Range (based on full-time 40 hours per week)

Annual Salary Range: $73,900 - $133,100

Offers will typically be made in the bottom half of the listed range. NREL takes into consideration a candidate’s education, training, and experience, as well as the position's work location, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee’s salary history will not be used in compensation decisions.

Benefits Summary

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. NREL 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.

* Based on eligibility rules

Submission Guidelines

Please note that in order to be considered an applicant for any position at NREL you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.

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EEO Policy

NREL is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.

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The National Renewable Energy Laboratory (NREL) is a leader in the U.S. Department of Energy’s effort to secure an environmentally and economically sustainable energy future. With locations in Golden and Boulder, Colorado, and a satellite office in Washington, D.C., NREL is the primary laboratory for research, development, and deployment of renewable energy technologies in the United States.

NREL is subject to Department of Energy (DOE) access restrictions. All candidates must be authorized to access the facility per DOE rules and guidance within a reasonable time frame for the specified position in order to be considered for an interview. DOE rules for site access during the interview process are the same regardless of whether the candidate is interviewed on-site, off-site, or via telephone or videoconference. Additionally, DOE contractor employees are prohibited from participating in certain Foreign Government Talent Recruitment Programs (FGTRPs). If a candidate is currently participating in an FGTRP, they will be required to disclose their participation after receiving an offer of employment and may be required to disengage from participation in the FGTRP prior to commencing employment. Any offer of employment is conditional on the ability to obtain work authorization and to be granted access to NREL by the Department of Energy (DOE). We understand that COVID-19 may have caused delays or closures at offices, consulates, and embassies. However, NREL cannot make exceptions to work authorization and access requirements, and exceptions to these requirements are not being made for COVID-19 related delays.

Please review the information on our Hiring Process (https://www.nrel.gov/careers/hiring-process.html) website before you create an account and apply for a job. We also hope you will learn more about NREL (https://www.nrel.gov/about/) , visit our Careers site (https://www.nrel.gov/careers/) , and continue to search for job opportunities (https://nrel.wd5.myworkdayjobs.com/NREL) at the lab.

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