Geospatial Data Scientist

We are seeking an experienced Geospatial Data Science Engineer to join our team. The ideal candidate will have a strong background in machine learning and geospatial data science, with experience working with ESRI products.

This is a unique opportunity to work on exciting projects and collaborate with our clients to develop innovative solutions using ESRI software.

The successful candidate will be responsible for:

• Working closely with clients to understand their needs and developing solutions using ESRI products
• Developing and pitching data science solutions by mapping business problems to machine learning or advanced analytics approaches
• Building high-quality analytics systems that solve our clients' business problems using techniques from data mining, statistics, and machine learning
• Writing clean, collaborative, and version-controlled code to process big data and streaming data from a variety of sources and types

Key Responsibilities:

• Consult closely with customers to understand their needs
• Develop and pitch data science solutions by mapping business problems to machine learning or advanced analytics approaches
• Build high-quality analytics systems that solve our customers' business problems using techniques from data mining, statistics, and machine learning
• Write clean, collaborative, and version-controlled code to process big data and streaming data from a variety of sources and types
• Perform feature engineering, model selection, and hyperparameter optimization to yield high predictive accuracy and deploy the model to production in a cloud, on-premises, or hybrid environment
• Implement best practices and patterns for geospatial machine learning and develop reusable technical components for demonstrations and rapid prototyping
• Integrate ArcGIS with popular deep learning libraries such as PyTorch
• Keep up to date with the latest technology trends in machine and deep learning and incorporate them in project delivery
• Support in estimation and feasibility for various RFPs

Required Skills and Qualifications:

• 5+ years of practical machine learning experience or applicable academic/lab work
• Proven data science and AI skills with Python, PyTorch, and Jupyter Notebooks
• Experience in building and optimizing supervised and unsupervised machine learning models including deep learning and various other modern data science techniques
• Expertise in one or more of the following areas:
• Traditional and deep learning-based computer vision techniques with the ability to develop deep learning models for computer vision tasks (image classification, object detection, semantic and instance segmentation, GANs, super-resolution, image inpainting, and more)
• Convolutional neural networks such as VGG, ResNet, Faster R-CNN, Mask R-CNN, and others
• Transformer models applied to computer vision
• Expertise in 3D deep learning with Point Clouds, meshes, or Voxels with the ability to develop 3D geospatial deep learning models, such as PointCNN, MeshCNN, and more
• A fundamental understanding of mathematical and machine learning concepts such as calculus, back propagation, ReLU, Bayes' theorem, Random Forests, time series analysis, etc
• Experience with applied statistics concepts
• Ability to perform data extraction, transformation, loading from multiple sources and sinks
• Experience in data visualization in Jupyter Notebooks using matplotlib and other libraries
• Experience with hyperparameter-tuning and training models to a high level of accuracy
• Experience in LLMs is preferred
• Self-motivated, life-long learner

Non-Negotiable Skills:

• Master's degree in RS, GIS, Geoinformatics, or a related field with knowledge of RS & GIS
• Knowledge and experience of ESRI products like ArcGIS Pro, ArcGIS Online, ArcGIS Enterprise, etc
• Experience with Image analysis and Image processing techniques in SAR, Multispectral and Hyperspectral imagery
• Strong communication skills, including to non-technical audiences
• Should have strong Python coding skills
• Should be open to travel and ready to work at client side (India)