AiDash is transforming Operations, Maintenance & Sustainability for core industries with geographically distributed assets using the power of Satellites and AI.
We help Fortune 500 companies utilize high-resolution satellite data for inspection and remote monitoring of geographically distributed assets at scale for utility and energy industries. Recommendations for preventive and predictive maintenance generated by our AI models have helped clients save millions of dollars.
Our team of researchers, engineers, data scientists, business consultants, and product managers constantly strive to build AI models and products, making the job of business executives and operating teams easier.
To fuel our capability and growth plans, last year we raised Series A funding round, led by Benhamou Global Ventures (BGV) and National Grid Partners (NGP), to give us both strategic and financial boosts. We are closing our Series B funding this quarter, led by the San Francisco Bay area’s leading sustainability-focused VC firm. We are growing at 400% since incorporation in 2019.
What you will be doing?
The goal of our engineering team is building best-in-class SaaS products backed by our proprietary AI models and complex geo-spatial datasets.
As Data Scientist at AiDash, you will be responsible for:
- Research & develop algorithms to model real world problems using Geospatial datasets. This includes data analysis, feature extractions, spatio-temporal analysis.
- Help develop, improve and evangelize our geospatial knowledge base and infrastructure.
- Design and develop APIs and SDKs for processing Geospatial datasets on scale.
- Work cross-functionally with data scientists and data engineers to integrate Geospatial models into the production pipeline.
- Work with data scientists and data engineers to translate existing geospatial algorithms into APIs and SDKs which can run on scale.
- Work with the team to develop and improve the algorithms for enhancing the quality of input datasets
What do you need for this position?
- PhD or MS with industry experience in engineering and related field with a focus on remote sensing and geospatial analysis.
- Coding proficiency with geospatial Python packages e.g. GDAL, rasterio, shapely, numpy, pandas.
- Experience working with a variety of satellite data types (e.g. optical, SAR, Lidar).
- Experience in implementation of AI/ML based models on Geospatial datasets.
- Experience in distributed computing for processing Geospatial datasets.