How to Crush Your Planet Interview: 22 Must-Know Questions and Answers

Looking to land a job at Planet? As an innovative leader in satellite imagery, Planet is a highly desirable company for remote sensing and data science professionals With competition fierce, acing your Planet interview is key to receiving an offer

This inside look at Planet’s interview process will help you enter the interview confidently prepared. I’ll walk through what to expect during a Planet interview, from the types of Planet interview questions you’ll face to the best way to answer them.

What to Expect in a Planet Interview

Planet’s interview process typically involves:

• A 30 minute phone screen with a recruiter
• A 1 hour technical phone interview
• A series of three 45-60 minute virtual interviews covering your experience and technical skills
• A final virtual interview where you’ll meet with the hiring manager

Interviews are conducted by phone or video call. You can expect Planet’s interviews to move quickly, with most candidates completing all rounds within 1-2 weeks of their initial phone screen.

Planet’s interview features a mix of technical questions and behavioral interview questions designed to assess your overall fit for the role. Expect questions that probe your expertise in:

• Remote sensing
• Satellite imagery
• Photogrammetry
• Programming languages like Python
• Cloud computing platforms like AWS
• Agile software methodologies

While Planet looks for candidates with outstanding technical abilities, they also want team members who embody their core values of transparency, objectivity, and ambition. Show them you possess the passion and persistence needed to overcome obstacles and rapidly iterate using agile principles.

Now let’s look at some of the most common Planet interview questions – and how to knock your answers out of the park.

22 Top Planet Interview Questions and Answers

Here are 22 of the top questions asked in Planet interviews, with tips on how to best demonstrate your abilities:

Technical Questions

1. Can you explain the pipeline or workflow involved in processing satellite imagery?

Planet’s interviewers want to understand your overall knowledge of how satellite systems work end-to-end. When answering:

• Walk through the high-level stages of the imagery workflow, from image capture by satellites to processing Raw imagery into usable products
• Elaborate on specific steps like radiometric and sensor corrections, orthorectification, atmospheric compensation, pansharpening, and data formatting
• For bonus points, touch on how techniques like photogrammetry are used to handle challenges with imagery like distortion or cloud cover
• Conclude by commenting on how this pipeline produces analysis-ready satellite imagery

2. How would you handle a situation where you need to process a large amount of data?

For this question, interviewers want to understand your approach to handling big data. A strong response would:

• Explain strategies for handling large datasets like dividing data into batches for parallel processing
• Discuss tools like Hadoop and Spark for scalable distributed processing
• Elaborate on cloud solutions like AWS that provide virtually limitless storage and computing resources
• Share any experience you have leveraging clusters and cloud platforms to process big data
• Emphasize how you would focus on optimization – utilizing available tools efficiently to reduce processing time and costs

3. Can you explain some of the tradeoffs involved when designing a satellite imaging system?

With this behavioral question, interviewers want to understand your systems analysis abilities. In your answer, be sure to touch on factors like:

• Resolution and swath width – the inherent tradeoff between level of detail and area covered
• Onboard storage capacity versus downlink availability
• Weight and power constraints that require balancing imaging payloads with other spacecraft systems
• Satellite orbit parameters like altitude and inclination which dictate revisit rate and coverage
• Production and launch costs which limit the feasible complexity of the system

Show you understand the nuances around balancing performance with practical constraints when developing imaging satellite architectures.

4. How would you go about orthorectifying a satellite image?

Orthorectification is about correcting distortion in imagery to create an accurate orthomosaic product. In your response, cover key steps like:

• Using ground control points and DEM data to model image distortion induced by terrain
• Georeferencing the raw imagery to the coordinate system
• Applying a warp transformation like polynomial or spline interpolation to remove distortion
• Resampling the image onto an orthorectified grid aligned to the map projection

For extra credit, mention factors that influence the orthorectification approach like required accuracy level and available ground reference data.

5. What are some common preprocessing steps used when analyzing multispectral or hyperspectral imagery?

Preprocessing is crucial to extract useful information from spectral imagery. Be sure to mention key techniques like:

• Radiometric calibration to convert sensor data to meaningful radiance units
• Atmospheric compensation to remove scattering effects
• Noise reduction to suppress errors and artifacts
• Band normalization, weighting, or enhancement to improve image interpretability
• Data transformation like vegetation indices to highlight features of interest

Discuss the value of these preprocessing steps in mitigating data quality issues prior to analysis.

6. How would you detect changes between two satellite images taken at different times?

Change detection is a common application of multi-temporal imagery. Discuss approaches like:

• Image differencing to directly subtract pixel values between two dates
• Image ratioing to divide pixel values and normalize changes
• Principal component analysis to isolate change information