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Temporary Python Matlab Jobs (NOW HIRING)

Boise State University

Post Doctoral Research Fellow

Boise, ID · On-site

$46.60K - $63.30K/yr

Serves in a temporary position that enables an individual with their Ph.D. to continue their ... Proficiency in programming and data analysis languages (LabVIEW, Python, MatLab, OriginPro, JMP, or ...

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How much do temporary python matlab jobs pay per year?

As of May 31, 2026, the average yearly pay for temporary python matlab in the United States is $139,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $164,500.00 per year, depending on experience, location, and employer.

What is the difference between Temporary Python Matlab vs Data Analyst?

AspectTemporary Python MatlabData Analyst
Required SkillsPython, MATLAB, scripting, data processingExcel, SQL, data visualization, statistical analysis
Work EnvironmentResearch labs, engineering firms, tech companiesBusiness, finance, marketing departments
CertificationsPython, MATLAB certifications often preferredNone mandatory, but certifications like CAP or Microsoft certifications helpful

Temporary Python Matlab roles focus on programming, data processing, and technical tasks in research or engineering settings. Data Analysts primarily interpret data to inform business decisions, often using Excel and SQL. While both roles involve data handling, Temporary Python Matlab positions are more technical and project-based, whereas Data Analysts work across industries analyzing data for strategic insights.

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Temporary Python Matlab jobs near you
Infographic showing various Temporary Python Matlab job openings in the United States as of May 2026, with employment types broken down into 27% Full Time, 68% Part Time, and 5% Contract. Highlights an 92% Physical, and 8% Hybrid job distribution, with an average salary of $139,971 per year, or $67.3 per hour.
Principal Engineer, State Estimation (R4602)

Principal Engineer, State Estimation (R4602)

Shield AI

San Diego, CA • On-site

$270K - $400K/yr

Full-time

Posted 1 hour ago

Job description

Founded in 2015, Shield AI is a venture-backed deep-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT and X-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With offices and facilities across the U.S., Europe, the Middle East, and the Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Job Description:
We are looking for an experienced state estimation engineer to design, develop, and support the deployment of safety-critical navigation solutions for aerospace platforms. This role requires deep expertise in state estimation theory, extensive practical experience implementing ownship navigation systems in the aerospace domain, and strong software development skills for production-quality navigation code. The engineer will design and implement a unified navigation architecture that supports traditional GNSS/IMU fusion while being extensible to all-source navigation strategies incorporating diverse sensing modalities for GPS-degraded and denied environments.
What you'll do:
Navigation System Architecture & Design:
  • Establish navigation performance requirements and error budgets for safety-critical applications
  • Support decomposition of navigation requirements into allocations for sensors, estimation algorithms, and software components
  • Design detailed software architecture for state estimation implementations, including module interfaces and data flow

Algorithm Development & Implementation:
  • Design and implement Extended Kalman Filter algorithms for navigation applications, with broad understanding of state estimation theory and alternative filtering approaches
  • Implement tightly-coupled and loosely-coupled GNSS/INS integration algorithms
  • Integrate diverse sensing modalities (vision, RF, celestial etc.) into multi-sensor fusion framework for GPS-degraded environments
  • Develop fault detection, isolation, and recovery (FDIR) strategies for navigation systems
  • Implement integrity monitoring and protection level calculations for safety-critical operations

Certification & Verification:
  • Develop verification and validation test plans for navigation algorithms
  • onduct performance analysis including Monte Carlo simulation, covariance analysis, and flight test data evaluation
  • Document navigation system design, requirements allocation, and compliance evidence
  • Support safety assessment activities including failure modes and effects analysis

Technical Leadership:
  • Provide technical guidance on navigation architecture and state estimation approaches
  • Support trade studies evaluating navigation sensor suites and fusion strategies
  • Mentor junior engineers on state estimation theory and implementation

Required qualifications:
  • MS or PhD in Computer Science, Software Engineering, Electrical Engineering, Aerospace Engineering, Mechanical Engineering, Applied Mathematics, or related field
    15+ years of experience developing state estimation algorithms for aerospace navigation applications
  • Demonstrated experience implementing GNSS/INS integration solutions
  • Experience with safety-critical system development and certification processes
  • Deep understanding of state estimation theory
  • Experience implementing multi-sensor fusion algorithms in production systems
  • Strong background in inertial navigation, GNSS positioning, and sensor error modeling
  • Strong programming skills in C/C++ and Python/MATLAB for algorithm development and analysis
  • Understanding of integrity monitoring, protection levels, and safety assessment methods
  • Experience with requirements management and verification/validation processes for certifiable systems
  • Understanding of GPS/GNSS signal structure, error sources, and performance characteristics
  • Knowledge of IMU error models, calibration, and Allan variance analysis
  • Familiarity with alternative navigation sensors (camera, RF ranging, celestial, etc.)
  • Understanding of navigation performance metrics (accuracy, integrity, continuity, availability)
  • Must be eligible to obtain a clearance

Preferred qualifications:
  • PhD in relevant field with focus on state estimation or navigation
  • Direct involvement in certified navigation system development from requirements through flight test
  • Experience with specialized navigation approaches (vision-aided navigation, terrain-referenced navigation, celestial navigation, etc.)
  • Publications or patents in navigation or state estimation
  • Experience with GPS/GNSS jamming and spoofing mitigation techniques

$270,000 - $400,000 a year
#LI-SM1
#LF
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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