Full/Part Time: Full-Time
The Data Sciences group in the Advanced Computing, Mathematics, and Data Division at PNNL seeks a Data Scientist to support their research effort in Data Analytics. This is an excellent opportunity to develop your scientific career in a world-class research institution by joining an interdisciplinary research team that focuses on accelerating data-driven scientific discovery. The primary emphasis of this position will be growing existing and developing new capabilities in the areas of Machine Learning and Deep Learning.
• 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.
Equal Employment Opportunity
Battelle Memorial Institute (BMI) at Pacific Northwest National Laboratory (PNNL) is an Affirmative Action/Equal Opportunity Employer and supports diversity in the workplace. All employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, marital or family status, sexual orientation, gender identity, or genetic information. All BMI staff must be able to demonstrate the legal right to work in the United States. BMI is an E-Verify employer. Learn more at jobs.pnnl.gov.
• BS/BA with 5 years of experience, or
• MS/MA with 3 years of experience, or
• PhD with 1 year of experience.
• PhD in Engineering or Science with 1+ years of experience.
• Strong publication record
• Experience in data analytics and data-driven modeling, in particular in the application of machine/deep learning to scientific domains of interest for PNNL such as chemistry, biology, energy, and environment.
Organization and Job ID
Job ID: 307537
Directorate: Physical & Computational Sciences
Division: Advanced Computing, Mathematics, and Data
Group: Data Sciences