Data Science / Machine Learning

Description At Sequoia Connect , we are a Talent-First Technology Ecosystem that redefines how elite professionals interact with the global digital landscape. We move beyond traditional models to act as a catalyst for the top 1% of global talent, connecting human potential with complex industrial execution. By joining our inner circle, you are not simply taking a position; you are aligning with a strategic partner dedicated to updating your "Human OS" and accelerating your growth through world-class, high-impact projects. We are currently partnering with a global IT powerhouse that represents the connected world through innovative, customer-centric experiences. As a USD 6 billion organization and one of the top 7 IT service providers globally, our client empowers over 1,200 global customers—including several Fortune 500 companies—to "Rise™." With a massive network of 163,000+ professionals across 90 countries, they are at the absolute forefront of digital transformation, leveraging next-generation technologies such as 5G, AI, Blockchain, and Quantum Computing. This is your chance to thrive in a workplace recognized as one of the most sustainable corporations in the world. You will join an environment that values innovation and societal impact, working on end-to-end digital transformation projects for global leaders. If you are a driven professional looking for global career opportunities and exposure to high-impact projects within an international network of expertise, this is where you belong. We are currently searching for a Data Scientist / Machine Learning Engineer: The Challenge (Responsibilities) 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 or 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. Your Profile (Requirements) 7+ years of applied data science / ML experience, with hands-on geospatial remote sensing . Strong Python programming skills, including numpy, rasterio/GDAL, xarray, scikit-image, and geopandas/shapely. Working knowledge of optical and SAR data (spectral indices, backscatter/dB, resolution trade-offs, revisit). Deep learning expertise with PyTorch , including experience fine-tuning models (transfer learning, LoRA/PEFT). Proven ability in model validation and calibration: ROC/AUC, thresholding, cross-validation, and handling weak/few labels. Experience with time-series / change-detection methods and coordinate reference systems (UTM, reprojection). High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery. Technologist DNA: A deep understanding of the difference between "coding" and "engineering." Desired Experience with InSAR / SAR offset tracking (SNAP, ISCE, or equivalent) for surface/structure displacement. Familiarity with geospatial foundation models (Prithvi-EO, TerraTorch, HLS) and segmentation. Knowledge of Copernicus/CDSE, Sentinel Hub, STAC, and Planetary Computer. Exposure to Aeolian geomorphology, dune dynamics, or the oil & gas / pipeline-integrity domain. Experience with MLOps and cloud environments (containerisation, scheduled inference, geospatial data pipelines). MSc/PhD in Remote Sensing, Geospatial Science, Earth Observation, CS/ML, Physics, or equivalent experience. Familiarity with cloud-native foundations or AI coding assistants. Languages Advanced Oral English: For seamless collaboration with global teams. Advanced Spanish. Special Notes Preference for candidates with Space Tech experience, though not mandatory. Work Arrangement We value flexibility to support your lifestyle. This position is available as: Remote . If you meet these qualifications and are pursuing new challenges, start your application on our website to join an award-winning employer. Explore all our job openings | Sequoia Career’s Page : https://www.sequoia-connect.com/careers/ Requirements 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).