Data Scientist II: Deep Learning for Undersea Acoustics

Pacific Northwest National Laboratory; Richland, Seattle (WA, WA); On-site; USD 114,000 - 182,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Pension plan

401(k) with match

Tuition assistance

Relocation assistance

Paid holidays

Vacation days

Job summary

Pacific Northwest National Laboratory is seeking a Data Scientist II to advance deep learning methods for undersea acoustics. You will analyze acoustic data, develop models, and test algorithms to detect and classify underwater sources in support of national security missions.

The role involves collaboration with ML engineers and researchers, with on-site work in Richland, WA or Seattle, WA, and opportunities to guide junior colleagues while ensuring safety and security requirements are met.

Qualifications

• BS/BA with 2 years data science experience OR MS/MA OR PhD.
• 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.

Responsibilities

• Develop, train, and evaluate deep learning methods for undersea acoustic detection, classification, localization, separation, and related problems.
• Formulate and investigate research questions through Fourier analysis, signal processing, mathematical analysis, algorithm development, and experiments.
• Design reproducible experiments and compare methods, examining detection and classification performance, false alarms, robustness to propagation and environmental variability, uncertainty, and computational demands.

Job description

Pacific Northwest National Laboratory is seeking a Data Scientist II to advance deep learning methods for undersea acoustics. You will analyze acoustic data, develop models, and test algorithms to detect and classify underwater sources in support of national security missions.

The role involves collaboration with ML engineers and researchers, with on-site work in Richland, WA or Seattle, WA, and opportunities to guide junior colleagues while ensuring safety and security requirements are met.