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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:
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We value flexibility to support your lifestyle. This position is available as:
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/
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).
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