Role: Geospatial Analyst
Employment Type: Full Time
Educational Qualification: Bachelor’s or Master’s degree in Geospatial Science, Remote Sensing, Agriculture Science, Engineering, Computer Science, or a related technical field.
Work Experience: 2 - 3 years of experience in geospatial analytics, applied remote sensing
within the Earth Observation industry
Role Description:
This role sits at the intersection of geospatial science, deep learning, and agriculture. You will
develop, train, and deliver ML/AI models and tools to extract features and value-added products
from multi-dimensional satellite data, with a strong focus on agricultural applications such as crop
mapping, yield estimation, and stress detection. You’ll work across the full pipeline from raw
imagery pre-processing through to production grade model deployment contributing directly to
Pixxel’s analytics platform and client-facing products.
Responsibilities & Duties:
Develop and operationalize agroecosystem models, data assimilation pipelines, and geospatial AI tools to extract agricultural and environmental from hyperspectral, multispectral, and SAR satellite/drone imagery.
A knack for moving quickly from concept to working prototype comfortable scoping and delivering Proof of Concepts (PoCs) and pilot projects under real-world constraints such as sparse or noisy ground truth data, ambiguous client requirements, and tight timelines. Thrives in situations where perfect data doesn’t exist and pragmatic, iterative problem- solving is required.
Design, experiment with, and validate deep learning models (CNNs, Vision Transformers, U-Nets, and emerging architectures) for crop type classification, crop stress detection, crop yield estimation, land use/land cover mapping, change detection, and urban monitoring.
Execute end-to-end client projects in the agriculture and land monitoring domains from requirement scoping and data acquisition through model training, field validation, and delivery of actionable geospatial intelligence.
Develop interactive geospatial visualizations, dashboards as needed and reports to communicate analytical results to technical and non-technical stakeholders, including farmers, agronomists, and policy makers.
Stay current with the rapidly evolving GeoAI landscape, including new model architectures, benchmark datasets, and cloud-native geospatial standards, and bring relevant innovations into Pixxel’s workflow.
Desirable Skills & Certifications:
Agriculture Domain Knowledge: Solid understanding of cropping patterns, crop phenological cycles, seasonal calendars, and farming practices. Demonstrated feel for the agriculture industry able to interpret satellite-derived insights in the context of real- world farming conditions.
Agriculture Project Experience: Hands-on project experience in at least two of the following: crop type classification, crop stress/health monitoring, crop yield estimation, soil moisture mapping, or farm-level advisory analytics using satellite imagery.
Remote Sensing & Spectral Analysis: Strong understanding of multispectral, hyperspectral, and SAR imagery, along with expertise in time-series analysis and multi-temporal compositing for crop and land monitoring
Machine Learning & Deep Learning: Practical experience with supervised and unsupervised classification, semantic segmentation, object detection, and change detection using frameworks such as PyTorch, TensorFlow, or scikit-learn. Familiarity with architectures like U-Net, ResNet, and Vision Transformers (ViT).
Programming: Proficiency in Python with geospatial libraries (Rasterio, GeoPandas,Shapely, xarray, GDAL/OGR) and ML libraries (PyTorch/TensorFlow, scikit-learn). Ability to write clean, modular, production-quality code.
Geospatial Data Handling: Minimum 2 - 3years of hands-on industry experience working with large raster (GeoTIFF, NetCDF) and vector datasets. Proficiency in pre-processing workflows including geo-referencing, atmospheric correction, geometric correction, radiometric calibration, and mosaicking.
GIS & Visualization: Proficiency with ArcGIS, QGIS, and/or PostGIS for spatial analysis and visualization.
Field Data Collection: Experience with ground truth and field data collection activities including GPS-based crop sampling, phenology observations, and canopy/soil measurements.
Analytical & Communication Skills: Strong spatial reasoning and pattern recognition ability. Good problem-solving skills and the ability to communicate complex geospatial findings clearly to diverse audiences through reports, presentations, and visualizations.
Publications in relevant journals/conferences is a plus.
Candidate Acumen:
Strong understanding of geospatial analytics, remote sensing, and GeoAI with hands-on experience in agricultural applications using satellite imagery and ML/deep learning models. Should be capable of independently driving end-to-end geospatial projects in fast-paced environments with strong problem-solving and communication skills.
Benefits:
Health insurance coverage
Unlimited leaves & flexible working hours
Role-based remote work and work-from-home benefit
Relocation assistance
Professional Mental Wellness services
Creche facility for primary caregivers (limited to India)
Employee Stock Options for all hires
About Pixxel:
Pixxel is a space data company and spacecraft manufacturer redefining Earth observation with hyperspectral imaging. The company’s first constellation of six commercial hyperspectral satellites—Fireflies—deliver imagery at 5-meter resolution and 135+ spectral bands, providing 50x richer detail than traditional Earth observation systems and unlocking insights across agriculture, climate, energy, environment, and more.
Once fully deployed, Pixxel’s constellation of 18–24 satellites will capture imagery across up to 250 bands in VNIR and SWIR ranges, with a 40 km swath and daily global revisit capability. Pixxel’s most unique strength is its full-stack approach, integrating every layer of the value chain from satellite hardware and manufacturing to AI-powered analytics.
Pixxel’s satellite constellation is complemented by Aurora, its in-house Earth Observation Studio that simplifies satellite imagery analysis and democratises remote sensing for all. Designed to make hyperspectral data more accessible, Aurora by Pixxel combines high-frequency imagery with AI-powered tools to generate actionable insights, even for users without technical backgrounds. The third pillar of Pixxel’s ecosystem is its in-house satellite manufacturing capability. Beyond building its own spacecraft, Pixxel also provides satellite systems and subsystems to other organisations. This dual capacity sets it apart in a sector where most companies focus on either payload design or data operations, but not both.
Pixxel’s team is young but deeply mission-aligned, with a culture rooted in curiosity, speed, and long-term thinking. As the company grows its constellation and expands Aurora, the focus remains on making space-based insights practical, scalable, and genuinely helpful so that the health of the planet becomes measurable and action becomes possible.
Pixxel was the only Indian startup selected for the Techstars Starburst Space Accelerator in Los Angeles and has been recognised in TIME’s Best Inventions of 2023, Fast Company’s Most Innovative Companies, and Via Satellite’s Top Innovators list.
Culture:
Pixxel is an organisation where we enable our employees to work on world-changing problems that they are passionate about, and a place where they can be their best selves day in and day out while ensuring they have fun every day.
Central to our employee-first ethos is a commitment to ensuring that every team member feels valued and heard. We nurture a healthy and supportive work environment where we prioritise well-being and growth in all aspects of life.
