Data Science / Machine Learning

Posted 3 Days Ago
Be an Early Applicant
Hiring Remotely in MEX
Remote
Senior level
Information Technology • Logistics • Professional Services • Consulting
The Role
Develop and calibrate change-detection and anomaly models on multi-temporal Sentinel-1/2 imagery to detect sand encroachment and pipeline displacement. Fine-tune geospatial foundation models, implement SAR displacement techniques, build dune-migration tracking, engineer Copernicus data ingestion, design labeling and validation strategy, and communicate results to stakeholders.
Summary Generated by Built In

Data Science / Machine Learning

We have an urgent requirement for a Data Scientist, preferably with Space Tech experience but not mandatory.# Data Scientist preferably with specialization in Geospatial / Remote Sensing

## About the role We are building a satellite-based early-warning system that detects wind-driven sand encroachment and pipeline displacement across a desert pipeline network, using Sentinel-1 (SAR) and Sentinel-2 (optical) imagery, foundation models, and physical dune-migration modelling. You will own the detection and calibration science: turning raw satellite passes into calibrated, validated alerts against real field-logged events.

What you will do - Build and calibrate change-detection and anomaly models on multi-temporal Sentinel-1/2 imagery over pipeline corridors. - Learn per-site """"normal terrain"""" baselines and validate detections against a ground-truth event log (detection rate, lead time, false-positive rate, AUC). - Fine-tune geospatial foundation models (Prithvi-EO / similar) with LoRA/PEFT on limited labelled data. - Implement SAR techniques for displacement: amplitude change, coherence, and pixel-offset tracking to measure pipe and dune movement. - Develop dune-migration tracking (optical flow / feature tracking), migration direction, and mobility indices. - Engineer robust ingestion from Copernicus (CDSE / Sentinel Hub / STAC) and fuse optical, SAR, DEM, and ERA5 wind data. - Design labelling strategy (encroachment masks, severity) and a train/validation split that avoids leakage. - Communicate results and limitations honestly to technical and business stakeholders.

Required -7+ years applied data science / ML, with hands-on geospatial remote sensing. - Strong Python: numpy, rasterio/GDAL, xarray, scikit-image, geopandas/shapely. - Working knowledge of optical and SAR data (spectral indices, backscatter/dB, resolution trade-offs, revisit). - Deep learning with PyTorch; experience fine-tuning models (transfer learning, LoRA/PEFT). - Model validation and calibration: ROC/AUC, thresholding, cross-validation, handling weak/few labels.- Time-series / change-detection methods and coordinate reference systems (UTM, reprojection).

Nice to have - InSAR / SAR offset tracking (SNAP, ISCE, or equivalent) for surface/structure displacement. - Geospatial foundation models (Prithvi-EO, TerraTorch, HLS) and segmentation. - Copernicus/CDSE, Sentinel Hub, STAC, Planetary Computer. - Aeolian geomorphology / dune dynamics; oil & gas or pipeline-integrity domain exposure. - MLOps and cloud (containerisation, scheduled inference, geospatial data pipelines).

Qualifications - MSc/PhD in Remote Sensing, Geospatial Science, Earth Observation, CS/ML, Physics, or equivalent experience

ADVANCED ENGLISH

REMOTE

Skills Required

  • 7+ years applied data science / ML with hands-on geospatial remote sensing
  • Strong Python (numpy)
  • rasterio / GDAL
  • xarray
  • scikit-image
  • geopandas / Shapely
  • Working knowledge of optical and SAR data (Sentinel-1/2, backscatter/dB, spectral indices)
  • Deep learning with PyTorch and experience fine-tuning models (transfer learning, LoRA/PEFT)
  • Model validation and calibration (ROC/AUC, thresholding, cross-validation, handling weak/few labels)
  • Time-series / change-detection methods and coordinate reference systems (UTM, reprojection)
  • MSc/PhD in Remote Sensing, Geospatial Science, Earth Observation, CS/ML, Physics, or equivalent experience
  • Advanced English
  • InSAR / SAR offset tracking (SNAP, ISCE, or equivalent)
  • Experience with geospatial foundation models (Prithvi-EO, TerraTorch, HLS) and segmentation
  • Familiarity with Copernicus/CDSE, Sentinel Hub, STAC, Planetary Computer
  • Domain knowledge: aeolian geomorphology / dune dynamics or oil & gas pipeline-integrity exposure
  • MLOps and cloud (containerisation, scheduled inference, geospatial data pipelines)
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The Company
21 Employees
Year Founded: 2016

What We Do

VALCE Talent Solutions is a recruitment agency and consulting firm specializing in IT talent acquisition and nearshoring, primarily in Mexico. They design customized solutions in IT talent and process optimization to help businesses scale intelligently and profitably. Their expertise focuses on specialized industries including Information Technology, Operations Management, and Supply Chain, providing end-to-end talent offerings to attract and retain top professional profiles.

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