Data Scientist - Electric Vehicle Charging

Full Job Description

Posting Title

Data Scientist - Electric Vehicle Charging

Location

CO - Golden

Position Type

Regular

Hours Per Week

40

Working at NREL

The National Renewable Energy Laboratory (NREL), located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for research and development of renewable energy and energy efficiency technologies.

From day one at NREL, you’ll connect with coworkers driven by the same mission to save the planet. By joining an organization that values a supportive, inclusive, and flexible work environment, you’ll have the opportunity to engage through our ten employee resource groups, numerous employee-driven clubs, and learning and professional development classes.

NREL supports inclusive, diverse, and unbiased hiring practices that promote creativity and innovation. By collaborating with organizations that focus on diverse talent pools, reaching out to underrepresented demographics, and providing an inclusive application and interview process, our Talent Acquisition team aims to hear all voices equally. We strive to attract a highly diverse workforce and create a culture where every employee feels welcomed and respected and they can be their authentic selves.

Our planet needs us! Learn about NREL’s critical objectives, andsee how NREL is focused on saving the planet.

Note: Research suggests that potential job seekers may self-select out of opportunities if they don't meet 100% of the job requirements. We encourage anyone who is interested in this opportunity to apply. We seek dedicated people who believe they have the skills and ambition to succeed at NREL to apply for this role.

Job Description

NREL’s Analysis of Vehicle and Infrastructure Deployment (AVID) Group in the Center for Integrated Mobility Sciences completes research and develops analytical tools to support the deployment of vehicle and infrastructure technologies in the near term. The AVID group builds tools and analytical frameworks that can be applied directly by end users to accelerate the deployment of clean vehicle and infrastructure technology. AVID works with domestic and international communities, public agencies, and private sector partners.

This position is intended to support transportation deployment projects within AVID Group. The successful candidate will be involved in projects that explore the soft costs associated with electric vehicle supply equipment (EVSE) installation as well as other analysis projects.

Below are the activities that could be completed by this candidate:

• Develop a database of EVSE installations from different sources like invoices from state and federal agencies as well as web sources.
• Develop a method to identify and analyze different cost components.
• Develop methods to quantify variations and uncertainties in cost components.
• Employ statistical and machine learning models to analyze uncertainties in the cost components.
• Develop a data pipeline to download raw data using an API.
• Develop image processing methods using high-performance computing services at NREL.
• Develop excellent visualizations to show the results of the analysis.
• Analyze telematics and fueling transaction data to determine EVSE requirements.
• Engage stakeholders and clients to keep projects relevant and robust.
• Collaborate across NREL and externally to develop and execute meaningful stakeholder engagement and community engagement.
• Support other NREL staff with transportation data analysis projects.
• Prepare project briefings and reports.
• Publish results of analysis.
• Represent NREL at key industry and client meetings.
  
  

Basic Qualifications

Relevant Master's Degree . Or, relevant Bachelor's Degree and 2 or more years of experience .

• Must meet educational requirements prior to employment start date.
  
  

Additional Required Qualifications

• Candidates must be familiar and have prior experience working with Python
• This position is expected to work an onsite hybrid work arrangement
  
  

Preferred Qualifications

• Degrees within in Data Science, Mathematics, Statistics, Engineering, Operations Research, Economics, Computer Science, or related field are preferred.
• Experience analyzing and working on uncertainty quantification and variations.
• Experience developing and using Monte Carlo and Markov Chain simulations.
• Experience developing Bayesian Neural Networks (BNN) and machine learning models for uncertainty quantification.
• Experience working with and developing raw datasets.
• Experience with machine learning models and statistical models.
• Excellent R or Julia programming experience.
• Experience with collaborative development of codes (Git and Github).
• Demonstrated capacity to learn on the job.
• Ability to summarize complex results and develop excellent visualizations.
• Comfort presenting in front of large audiences.
• Strong oral communication skills.
• Strong writing skills.
  
  

Job Application Submission Window

The anticipated closing window for application submission is up to 30 days and may be extended as needed.

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

Job Profile: Researcher II / Annual Salary Range: $73,200 - $120,800

NREL takes into consideration a candidate’s education, training, and experience, 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
  
  

Drug Free Workplace

NREL is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.

If you are offered employment at NREL, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.

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.

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, domestic partner 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.

EEO is the Law |Pay Transparency Nondiscrimination |Reasonable Accommodations

E-Verify For information about right to work, click here for English or here for Spanish.

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.

#J-18808-Ljbffr