Software, data & the business
Science, Imaging & Earth Data
Turn satellite images and sensor data into maps, measurements and intelligence, and help design the instruments.
What it is
Science, imaging and Earth data is the work of getting useful answers out of what satellites see. Scientists and data specialists calibrate cameras and radar instruments, process raw images into accurate, map-ready products, and build analysis (often with machine learning) that detects fires, ships, crops or changes on the ground. Mission and instrument scientists decide what a new satellite should measure and how to prove it measures it correctly.
What you actually do
- Process raw satellite imagery into calibrated, georeferenced products using Python libraries such as GDAL and Xarray.
- Develop and validate algorithms that turn images into higher-level products, such as fire detections, cloud maps or change alerts.
- Train and test machine learning models for object detection, change detection and time series analysis, and run them at large scale in the cloud.
- Define how an instrument is calibrated (radiometric and geometric) and plan the ground tests that check it.
- Analyze optical and radar (SAR) imagery for customers in defense, intelligence, agriculture or disaster response, and report what you found.
- Write algorithm and product documentation and present results to customers, engineers and product teams.
A day of this work, concretely
Build a wildfire detection product
A new infrared satellite starts sending down calibrated images. You prototype an algorithm that flags hot pixels as possible fires, compare its detections against known fires to measure false alarms, and then turn the prototype into production code that runs on every new image. You document the method so customers know how far to trust each detection.
Check an instrument's calibration before launch
Before the camera is integrated into the spacecraft, you write the procedure for measuring its response with calibration equipment such as integrating spheres and blackbodies. During the test you watch the data come in, then compute calibration coefficients and their uncertainty. After launch you compare on-orbit images with known targets to see whether the calibration held.
Deliver change detection for monitored sites
A government customer wants to know when construction starts at a list of locations. You run a change detection model over months of imagery, review the flagged changes by eye to remove false alarms, and deliver a short report with before and after images. Missed or wrong detections go back into training the next version of the model.
Is it right for you?
Most people here studied remote sensing, geography, physics, atmospheric or Earth science, engineering or data science, and many hold a master's or PhD; research scientist and postdoc roles in particular ask for a doctorate, while instrument scientist roles may instead ask for years of calibration experience. Data scientists and machine learning engineers from other industries move in by learning geospatial data formats and how satellite sensors work. People who thrive are careful about measurement and uncertainty, enjoy writing code as much as doing science, and can explain results to non-specialists.
You will likely enjoy it if
- You enjoy working with images, maps and measurements and want to know exactly how accurate they are.
- You write Python comfortably and want to use it on real sensor data rather than practice datasets.
- You like explaining technical results to customers and product teams, in writing and in meetings.
- You already have, or are willing to earn, a graduate degree for research scientist roles.
What you need
- Degree in remote sensing, geography, physics, Earth or atmospheric science, engineering, computer science or a related field; many roles ask for a master's or PhD, or a bachelor's plus several years of experience
- Strong Python for scientific data analysis
- U.S. person status for roles that touch export-controlled data or instruments
- For defense and intelligence work: ability to obtain and keep a U.S. security clearance
Skills that help
How to get started
- 1Learn how satellite sensors work (optical, infrared and radar) through a free course such as NASA's ARSET remote sensing trainings.
- 2Download free imagery (Landsat from USGS EarthExplorer, Sentinel data from the Copernicus Data Space Ecosystem) and practice processing it in Python with GDAL and Xarray.
- 3Build two or three portfolio projects from raw data to finished result, for example a burn scar map, a crop change analysis or a ship detection model, and publish the code with a short write-up.
- 4Decide whether you need a graduate degree: research scientist and postdoc roles do, while instrument, data product and machine learning roles often weigh experience and a portfolio alongside a degree.
- 5Learn cloud-scale processing (AWS or GCP, Docker), because postings expect algorithms to run on large volumes of imagery, not one scene at a time.
- 6Apply to roles titled remote sensing data scientist, geospatial analyst, imagery analyst, machine learning engineer or instrument scientist, and if you hold a PhD, look at postdoc openings at research labs such as JPL.
Common misconceptions
Myth: This work is only for astronomers and astrophysicists.
Reality: Most of it points the other way, at Earth. Employers hire remote sensing, geography, atmospheric science, physics, engineering and data science backgrounds to measure fires, weather, crops, ships and construction.
Myth: A good machine learning model is enough.
Reality: Postings stress validation, calibration and understanding how an algorithm fails. A model that scores well on a test set can still fail on a new sensor, season or region, so much of the job is checking results against ground truth.
Myth: Every role requires a PhD.
Reality: Research scientist and postdoc roles do, but data product, geospatial software, instrument and analyst roles also take a bachelor's or master's with relevant experience. Some government imagery analyst openings have accepted years of imagery analysis experience in place of a degree.
What it pays
Science & Data work typically pays $119k–$223k/yr today, with a live median of $153k/yr across the 77 open roles that state their pay.
What our research measures about science & data work
Read from the open postings on 2026-10-29 by our space industry research, rebuilt every day. Every figure opens the row of the report it comes from.
- Who is hiring119 open roles (1.5% of the space roles we read) at 23 employers, 41 of them posted in the last 30 days.
- Where the jobs are16.0% of these roles are remote; the rest are on-site or hybrid.
- Who can apply68.1% of the postings are open only to US persons or US citizens, and 37.2% name a security clearance.
- Skills and toolsThe skills its postings name most: Python (71%), C or C++ (27%) and SQL (18%).
- Degrees and experience1.8% of the postings take a high school diploma or an associate's degree, 64.6% name a master's or PhD, and they ask for a median of 3 years of experience at the least.
- Pay transparency64.7% of the postings state their pay, at a median $153,000 a year.
- Internships and entry level8 open roles are for someone starting out (6.7% of its open roles).
- Shifts, weekends and travel4.4% of the postings ask for weekend work, 4.4% for overtime or extended hours.
Frequently asked questions
Do I need a PhD to work in remote sensing at a space company?
Not always. Research postdoc roles require a PhD, instrument scientist roles may ask for a physics or engineering degree plus years of calibration experience, and remote sensing data scientist postings often accept a PhD, a master's with industry experience, or a bachelor's with more years of experience. A strong portfolio built on real satellite data counts for a lot at the bachelor's and master's level. The board lists 128 open science and imaging roles today, so you can compare what they ask for.
Where can I get satellite data to practice on?
Landsat imagery in the USGS archive has been free to download since 2008, through tools such as EarthExplorer (USGS Landsat data access). The Copernicus Data Space Ecosystem gives free access to data from the European Sentinel missions. NASA's ARSET program offers remote sensing trainings at no cost, including a self-paced fundamentals course.
Do geospatial intelligence jobs need a security clearance?
Many do. Defense and intelligence analytics roles at commercial imagery companies often ask that you can obtain and keep a U.S. clearance, and imagery analyst openings at the National Geospatial-Intelligence Agency have required U.S. citizenship, a Top Secret/SCI clearance and a polygraph. The ITAR and security clearance guide explains how clearances and export rules affect hiring.
Is there a certification for geospatial intelligence?
The postings for these roles hire on degrees, portfolios and experience rather than a specific certificate. USGIF has temporarily suspended its Certified GEOINT Professional program and says it is reviewing the program's future. Your time is better spent on projects with real imagery and on the Python and machine learning skills postings name; the guide on how to get a job in the space industry covers the rest of the search.
Related kinds of work
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Launch & Mission Operations
Run the launch pad, the countdown and the spacecraft in orbit, often on shifts around the clock.