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Veris
About UsVeris is a market leading national survey, spatial and planning business. With over 450 professionals working across Australia Veris combines innovative technologies with some of Australia’s best spatial exper…
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About the role
About UsVeris is a market leading national survey, spatial and planning business. With over 450 professionals working across Australia Veris combines innovative technologies with some of Australia’s best spatial experience to deliver an integrated approach to the full project life cycle, from initial planning and feasibility through to construction and beyond.
The OpportunityAs a Spatial Data Scientist you will be involved in solving our clients’ problems and developing novel spatial solutions. This will primarily involve feature extraction from 3D point clouds and imagery gathered from mobile mapping systems, UAVs and other capture systems.
Your activities at Veris will involve:Developing innovative solutions to complex geospatial problemsResearching and advising on the options and recommending solutions for solving the problemsIdentifying all the relevant data sources to solve the business needsBuilding spatial analytics, predictive models and/or machine learning algorithms to extract features from our captured spatial data, particularly point clouds and drone imageryDeveloping and/or extending web platforms to solve a range of client needsProcessing, cleansing & verifying spatial datasets
About YouAs a client facing business it is essential that you are actively involved with Veris’ clients. You will be an active team member, and as a senior member of the team will mentor and guide less experienced team members. You will also support senior leaders to engage with clients on a range of spatial problems. The role will involve creating reports, visualisations and industry presentations.Experience you will need:
Highly desirableDemonstrated experience in computer vision including image classification, object detection, semantic segmentation, feature extractionDemonstrated experience in 3D point cloud/mesh model processing, analysis, and automationExperience designing, implementing, or maintaining geospatial data pipelines using orchestration and workflow tools such as Prefect, or equivalent systems.5+ years of professional experience as a Machine Learning Engineer, Data Scientist, or in a closely related role, with demonstrated experience building and deploying production machine learning or deep learning models.Strong problem-solving skills with the ability to work through ambiguous or complex technical problems and develop practical solutions.Curious and proactive approach to learning, experimentation and continuous improvement, with a willingness to explore new technologies and approaches.Experience in ML training, evaluation, deployment, and optimisation.Professional experience with ML and deep learning frameworks such as PyTorch, TensorFlow, or comparable tools.Ability to identify performance bottlenecks and improve inference speed and resource usageExperience with QGIS or comparable geospatial visualization and analysis software.Strong proficiency in Python and geospatial Python libraries such as rasterio, geopandas, shapely, GDAL, or equivalent technologiesSolid understanding of 2D and 3D geospatial data structures, formats, processing workflows, and analysis techniques.
Our CultureAt Veris we value providing a diverse and inclusive workplace where every individual is treated with dignity and respect. We are an Equal Opportunity employer and all qualified applicants will receive consideration for employment regardless of their race, cultural background, ethnicity, national origin, ability/disability, gender identity, sexual orientation, spirituality or religion and encourage applicants from diverse backgrounds, communities and industries.
We respect and honour Aboriginal and Torres Strait Islander Elders past, present and future. We acknowledge the stories, traditions and living cultures of Aboriginal and Torres Strait Islander peoples on this land and commit to building a brighter future together.
sign in above to apply · via LinkedIn
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