Senior Data Scientist III - Machine Learning for Undersea Acoustics

Overview At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget. Our Science & Technology directorates include National Security, Integrated Discovery Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus. The National Security Directorate (NSD) drives science-based, mission-focused solutions to take on complex, real-world threats to our nation and the world. The AI and Data Analytics Division, part of the National Security Directorate, combines profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytic challenges. Working in multidisciplinary teams, we connect foundational research to engineering to operations, providing the tools to innovate quickly and field results faster. Our strengths are integrated across the data analytics lifecycle, from data acquisition and management to analysis and decision support. Responsibilities PNNL is seeking a Senior Data Scientist III with deep learning expertise and experience applying Fourier analysis or signal processing to acoustic or related sensor data. You will lead the development, training, and evaluation of deep learning models to detect, classify, localize, or characterize underwater sources. This research supports national security and naval sensing missions. In the AI and Data Analytics Division, you will lead research projects or major parts of larger projects, developing analytical methods from initial questions through evaluation and research prototypes. Current priorities include applying deep learning to undersea acoustic data and using Fourier analysis or signal processing to develop and evaluate methods for detecting, classifying, or characterizing underwater sources. The role also offers opportunities in time-series analysis, representation learning, anomaly detection, uncertainty quantification, and multimodal sensing. Candidates with deep learning experience in undersea acoustics, sonar, audio, radar, seismic, or related sensing applications are encouraged to apply. The role may also include leading the evaluation of agentic AI systems that integrate deep learning with acoustic analysis tools. You will work alongside researchers and domain specialists on difficult national science and technology challenges. Collaboration with software and machine learning (ML) engineers will reflect each project's needs and stage of development. Opportunities to advance existing research and pursue new ideas may come through ongoing projects, internal research investments, or new proposals. Key Responsibilities • Lead the development, training, and evaluation of deep learning methods for undersea acoustic detection, classification, localization, and related problems using Fourier analysis or signal processing, mathematical analysis, and experiments. • Lead research projects or major technical efforts, coordinate contributors, and plan the work, resources, and milestones. • Evaluate methods against baselines using representative data, examining detection and classification performance, false alarms, robustness to propagation and environmental variability, uncertainty, and computational demands. • Build and validate research prototypes and evaluate agentic AI systems with software and ML engineers, addressing technical barriers to transition and deployment. • Work with mission partners and domain specialists to turn user needs into research questions, and communicate findings through analyses, technical reports, and discussions. • Develop research ideas and collaborate with project leaders on proposals to support your research. • Mentor colleagues, help recruit and onboard researchers, and share methods and findings across disciplines. • Follow applicable quality, safety, and security requirements. This position is based in either Richland, WA or Seattle, WA and requires an onsite presence. Qualifications Minimum Qualifications: • BS/BA and 5+ years of data science experience -OR- • MS/MA and 3+ years of data science experience -OR- • PhD with 1+ year of data science experience • Experience developing, training, and evaluating deep learning models for acoustic, sonar, audio, radar, seismic, or related sensor data. • Experience implementing, training, and evaluating deep learning models in Python with PyTorch. Preferred Qualifications: • Experience developing and evaluating deep learning methods for undersea acoustic detection, classification, localization, or related problems. • Experience applying Fourier analysis or other signal processing methods to acoustic or related sensor data. • Experience with time-frequency representations or array-processing methods for acoustic analysis. • Familiarity with agentic AI systems and methods for evaluating their performance and reliability. • Familiarity with national security applications of deep learning and undersea acoustics and submitting proposals. Hazardous Working Conditions/Environment Not applicable. Additional Information This position requires the ability to obtain and maintain a federal security clearance. A security clearance background investigation includes review of your employment, education, financial, and criminal history, as well as interviews with you and your personal references, neighbors, and co-workers to determine trustworthiness, reliability, and loyalty to the United States. The investigation also examines your foreign connections, drug and alcohol use, foreign influence, and overall conduct. Requirements: • U.S. Citizenship • Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibili