Statistical Signal Processing Researcher - Monterey, CA
$123,219–$236,579 year
On-site · Monterey, California, United States
Job Summary
Statistical Signal Processing Researcher responsible for deriving optimal mathematics for novel statistical signal processing / communications problems from first-principles, developing expressions describing statistical performance of new algorithms, and evaluating computational requirements versus baselines. Communicates highly technical concepts to technical and non-technical audiences, understands customer/operational requirements, and adapts systems accordingly. Key skills include stochastic signal processing, detection and estimation theory, linear algebra, link-budget analysis, and proficiency with C/C++, Python, and MATLAB. Candidates should demonstrate independent research capability, strong problem-solving, and collaborative teamwork in a high-security, research-oriented environment. Preferred candidates may hold a Ph.D. and have publications, plus familiarity with fast signal processing algorithms, optimization theory, information theory, electromagnetic propagation, sensor array processing, Linux development tools. Salary range: $123,219 - $236,579 with comprehensive benefits.
Required Qualifications
- Active Top Secret security clearance with SSBI and SCI eligibility.
- Master's degree in electrical engineering, applied mathematics, statistics or closely related field
- Minimum three (3) years of experience
- Proficiency with stochastic signal processing and digital communications
- Proficiency with detection and estimation theory
- Proficiency with linear algebra
- Experience with link budget analysis
- Proficiency with C/C++, python, and MATLAB
- Exceptional analytical and problem-solving skills
- Good organization, decision making, and verbal/written communication skills
- Demonstrated ability to perform independent research
- High level of self-motivation and ability to work under minimal supervision
- Ability to work effectively in small team settings to solve complex problems
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