ResponsibilitiesThe
Data Sciences & Machine Intelligence Group in the Advanced Computing, Mathematics, and Data Division at PNNL seeks a
Data Scientist 3 to join the group to lead and support scientific research in the broad areas of data science, artificial intelligence (AI) and machine learning (ML) with a focus on optimization/controls and continual learning for complex systems (e.g. DOE Scientific User Facilities - particle accelerators, etc.) and data science for scientific domains. This is an excellent opportunity to develop your scientific career in an outstanding research institution by joining an interdisciplinary research team that focuses on accelerating scientific discovery. The emphasis of this position will be growing existing and crafting new capabilities in the areas of AI, scientific machine learning, optimization/controls, continual learning and agent development to strengthen the group's leadership position in data science and machine intelligence. A successful candidate will have demonstrable expertise in the broad areas of data science and deep reinforcement learning, graph neural networks. We are looking for a proactive, highly motivated individual with an aptitude for contributing on multi-disciplinary teams, and an interest in natural sciences.
- Designs, develops, and implements methods, processes, and systems to analyze diverse data.
- Applies knowledge of statistics, machine learning, advanced mathematics, simulation, software development, and data modeling to integrate and clean data, recognize patterns, address uncertainty, pose questions, and make discoveries from structured and/or unstructured data.
- Produces solutions driven by exploratory data analysis from complex and high-dimensional datasets.
- Designs, develops, and evaluates predictive models and advanced algorithms that lead to optimal value extraction from the data.
- Demonstrates ability to transfer skills across application domains.
QualificationsMinimum Qualifications:
- BS/BA and 5+ years of relevant experience -OR-
- MS/MA and 3+ years of relevant experience -OR-
- PhD with 1+ year of relevant experience
Preferred Qualifications:
- Degree in Data Science, Computer Science, Electrical and Computer Engineering, or a closely related field.
- Experience in the DOE national lab system.
- Demonstrated experience in conducting scientific exploration and research through artifacts such as scientific publications in top tier venues (*ACL, EMNLP, AAAI, NeurIPS, ICLR, LREC, etc.) and publicly released datasets and/or software tools.
- Architect and build deep reinforcement learning and continual learning for scientific domains.
- Proficiency in computer science engineering skills.
Hazardous Working Conditions/EnvironmentNot Applicable
Testing Designated PositionThis is not a Testing Designated Position (TDP).
Rockstar RewardsEmployees and their 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.
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Notice to ApplicantsPNNL lists the full salary range for each position in accordance with Washington State pay transparency requirements.
While the full range is posted, starting salaries generally fall between the minimum and midpoint of the range, with individual offers determined based on relevant job-related experience, qualifications, internal pay equity, and available budget. This approach applies to all positions except those governed by collective bargaining agreements and certain limited-term positions with specific pay rules.
As part of our commitment to fair compensation practices, PNNL does not ask for or consider current or past salary when making compensation offers. Instead, offers are based on the requirements of the position, relevant job-related skills and experience, prevailing market conditions, internal pay equity, applicable collective bargaining agreements, and available budget.
Minimum SalaryUSD $140,200.00/Yr.
Maximum SalaryUSD $228,800.00/Yr.