Spectral Scientist

Arena Technical Resources, LLC (ATR); Springfield (VA); On-site; USD 80,000 - 140,000; Full time

Job summary

An established industry player is seeking a Sr. Spectral Scientist with expertise in atmospheric research and hyperspectral data processing. This exciting role involves designing and implementing advanced software tools and algorithms that enhance intelligence analysis for the DoD and IC communities. You will collaborate with a skilled team, applying your knowledge of atmospheric correction techniques and programming to develop innovative solutions. If you are passionate about advancing research in this field and thrive in a collaborative environment, this opportunity is perfect for you.

Qualifications

• Active TS/SCI Security Clearance is required.
• Experience in atmospheric correction techniques and hyperspectral data analysis.

Responsibilities

• Conduct research on radiative transfer theory for atmospheric correction.
• Implement software tools using Python, C++, or ENVI/IDL.

Skills

Atmospheric correction techniques

Python programming

C++ programming

ENVI/IDL

Remote sensing techniques

Hyperspectral image processing

Data calibration

Education

Ph.D.

M.A./M.S.

B.A./B.S. Degree

Tools

ENVI/IDL

Job description

Title: Sr. Spectral Scientist

Location: Springfield, VA

Eligibility/Clearance: This position requires an active TS/SCI clearance

Job Description:

We are seeking an experienced Spectral Scientist who specializes in Atmospheric Research to support a large R&D program that is focused on providing advanced intelligence analysis for the benefit of the DoD and IC communities.

You will play a critical role in designing, developing or enhancing, and implementing cutting-edge software tools and algorithms for hyperspectral data processing.

Your primary area of responsibility will be to research, develop, and implement algorithms into functional software tools and plugins for hyperspectral data. You will work with atmospheric correction techniques, including QUAC, QUAC-LSP, FLAASH, and others, to enhance and validate results across multiple algorithms. Collaboration with a highly skilled team is key, as you will contribute to tools used across the analytic community and ensure their accuracy and effectiveness.

Key Responsibilities:

1. Conduct research on radiative transfer theory as it applies to atmospheric correction for hyperspectral data.
2. Implement software tools using Python, C++, or ENVI/IDL.
3. Design and refine target detection algorithms, applying your understanding of physics and spectral phenomenology.
4. Develop and implement new software tools and techniques for data processing, calibration, and atmospheric correction.
5. Build or enhance, test, and validate software tools to ensure performance and accuracy.
6. Document your work in software deliverables with proper technical documentation.
7. Present your research, methodologies, and findings to different audiences.
8. Collaborate with teams across the Department of Defense (DoD) and Intelligence Community (IC) to effectively integrate tools and solutions.

Required Security Clearance, Education and Experience (you must meet one of the following combos):

1. For the SME Level:
   - Ph.D. and 10 years of experience or
   - M.A./M.S. and 18 years of experience or
   - B.A./BS Degree and 22 years of experience
2. For the Senior Level:
   - Ph.D. and 2 years of experience or
   - M.A./M.S. and 6 years of experience or
   - B.A./BS Degree and 10 years of experience
3. For the Mid-Level:
   - Ph.D. and 0 years of experience or
   - M.A./M.S. and 4 years of experience or
   - B.A./BS Degree and 4 years of experience

- Active TS/SCI Security Clearance.

Required Skills:

1. Past demonstrated experience with atmospheric correction techniques, such as QUAC, FLAASH, or QUAC-LSP.
2. Strong programming skills in Python and ENVI/IDL.
3. Background in remote sensing techniques, especially with hyperspectral image processing techniques and data calibration.
4. Demonstrated experience developing tools for hyperspectral data analysis.
5. Ability to process, exploit, and disseminate analytical results.

Desired Bonus Skills:

1. Familiarity with Long Slant Path (LSP).
2. Familiarity with the SAINT tool.
3. Familiarity with GeoReplay.
4. Familiarity with Hierarchical Data Format (HD5, HDF5, etc.) containing multidimensional arrays of scientific data.