Data Science / Machine Learning

Location: México (MX)

Experience Level: Senior

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).