Developed complete end-to-end Python tools with web user interfaces, command-line applications (open-source libraries, ArcGIS API for Python, and ArcPy) to automate complex geospatial workflows, reducing manual processing time from several hours to few minutes. Spearheaded internal technical presentations across the practices to demonstrate the capabilities of custom automation tools, Python, GDAL, and open-source software, fostering a culture of continuous learning, and mentoring team members on advanced GIS capabilities. Engineered automated data pipelines to streamline data analysis and preprocessing via OData Feeds and APIs, successfully transforming historical data and diverse file formats (e.g., PDFs, Excel) into standardized, usable databases while maintaining strict quality assurance. Programmed dynamic GIS solutions and reporting systems that instantly generate standalone HTML reports, static cartographic products, and interactive web dashboards, enabling multi-disciplinary teams to easily visualize and interpret large spatial datasets. Built end-to-end machine learning pipelines to process massive datasets, including aerial, satellite, and drone imagery, completely automating the extraction of spatial insights. Collaborated closely with multi-disciplinary project teams (including planners and engineers) to design geospatial strategies, actively contributing to technical workflow documentation, project proposals, effort estimation, and budgeting to align custom solutions with client goals. Provided comprehensive technical support and served as a key GIS contributor on complex projects, offering expertise in spatial analysis, desktop GIS workflows, and rigorous QA/QC procedures to ensure all technical deliverables met industry standards.

Played a key role in conceptualizing and crafting innovative project workflows that improved efficiency, alignment with client needs and industry standards; Assisted in drafting various project proposals that secured more than $400,000 CAD funding from government agencies. Contributed efficient, timely, and reliable ideas for research and development by employing python workflows to automate diverse image processing, geoprocessing, and AI/ML tasks. Developed remote sensing based AI products using test-driven development with pytest, and mlflow to track experiments for better model performance improvement and optimization. Migrated an entire product’s codebase from Java to Python with few parts of the product in Rust, improving code security and maintainability to enhance rapid prototyping and testing. Designed Python workflows to automate downloading and pre-processing satellite imageries. Mentored interns by actively guiding project workflows and conducting thorough code reviews. Actively participated in the continuous improvement of development processes by proposing and implementing innovative solutions. Adhered to GitHub workflows to enhance project features through structured pull requests and code reviews. Utilized Kanban boards and Agile methodologies for effective project management, facilitating smooth team coordination and timely delivery of project milestones. Proactively researched and recommended new technologies and tools to improve development processes, identifying solutions that streamlined workflows and improved efficiency. Reviewed remote sensing and deep learning literature papers, implementing and evaluating deep learning models using AI frameworks. Conducted both visual and statistical interpretations of results and probability maps, examining model performance. Inspected and fine-tuned training data for ML models, preparing imagery and extracting features for ML and deep learning tasks using Python. Created aesthetic map layouts and effectively managed ArcGIS Pro projects, geodatabases, imagery, and results. Effectively developed Python scripts that adhere to PEP8 style guidelines, maintaining and collaborating on code with the team using GitHub.

Prepared detailed step-by-step procedural lab materials using Catalyst (formerly, Geomatica). Conducted weekly in-person labs, provided guidance and support to a class of 30 students for performing their tasks and assignments. Evaluated their work and provided feedback to help improve their understanding and performance about various remote sensing concepts.

Generated a Network Dataset for performing network analysis by integrating road layers of New Brunswick from multiple sources using ArcGIS Desktop. Developed ArcPy scripts to conduct QA/QC and verify the connectedness of the network dataset. Created an ArcPy workflow to merge layers and tables using attribute and spatial relationships.

Performed terrestrial laser scanning raw data conversion to LAS format using Faro Scene; developed reports and screenshots using CloudCompare as required by the supervisor; provided assistance in creating powerpoints, reports, organising digital files and media. Developed various interactive 3D models using the Sweet Home 3D software; developed a website to showcase all the generated models.

Development of risk raster models using spatio-temporal datasets; provided assistance in spatial data organization and management. Development of python, shell scripts for automating scheduling, batch processing and workflow automation on the AWS EC2 instances. Performed spatial analysis and image processing tasks using python and GRASS GIS; provided support in generating results and reports. Better understanding of the end user’s request and come up with an optimal solution for all the spatial related real world GIS problems.

Developed a django app to visualize the user uploaded seismic data, perform filtering, compute codaQback and download results.