Job opportunities at Thaicom
Available Position 1 = Forest Carbon Remote Sensing Scientist
Responsibilities
Develop, test, and improve techniques for mapping forest carbon using data from satellite images.
Validate the results of the forest carbon mapping against a variety of independent datasets.
Source and synthesize existing and new field data on forest parameters.
Produce reports and documentation, including articles for use in internal and external product and process.
Interact with current and potential clients to explain our procedures
Track advances in volunteer carbon protocols and incorporate into product strategy.
Review scientific literature for novel approaches and best practices for forest carbon mapping.
Required skills and qualifications
Master degree or higher (> 2 yrs) related to forest carbon science. Very flexible here; fields can include ecology, forestry, carbon project development/verification/auditing
Experience with forest allometry and growth models
Expert in using traditional statistics, geostatistics or machine learning to analyze large spatial datasets
Skilled in programmatic geospatial data analysis and visualization
Preferred skills and qualifications
Python , R programming expertise, especially with open source geospatial libraries
Experience in remote sensing image analysis (satellite, airborne or UAV platforms)
Experience in Google Earth Engine
Detailed understanding of voluntary carbon market protocols both domestic and international standard
Available Position 2 = Remote Sensing Data Analytics
Description:
We are looking for an expert in remote sensing data analytics to help us extract value from remote sensing data. You will lead all the analytics process, applying remote sensing data to answer customer’s pain points. Deeply research in remote sensing model and work with Data Science team to build models for agriculture and environment.
Responsibilities:
- Mines, retrieves, and applies statistical and mathematical analyses to remote sensing data, spatial and non-spatial data from internal and external databases to identify trends, solve analytical problems, derive insights, and inform decision-makers especially for agricultural and environment sector.
- Performs difficult technical research and project development related to complex GIS, remote sensing data and data analysis related problems. Evaluates alternatives and recommend effective courses of action. Serves as a technical resource on difficult technical issues. Prepares and maintains technical documentation and accurate, organized records.
- Identify and report new initiatives and performs program and business process improvement.
- Supervise multiple projects and allocates/balances resources assigned, identifies interdependencies, identifies/ mitigates/ manages risks, prepares action plans, resolves problems and takes corrective measures, produces/oversees main program documentation, and ensures effective communication between stakeholders
Requirements:
- Experience working with remote sensing analysis in agricultural or environmental
- Experience in using open-source GIS software, ArcGIS, Google Earth, Google Earth Engine
- Experience building land use and land cover change maps using different sources of satellite imagery including multispectral imagery Experience building land use and land cover change maps using different sources of satellite imagery including multispectral imagery
- General understanding of Python is desirable
- Demonstrated ability to analyze large complex datasets (eg.country scale with multi-temporal dataset)
- Strong scientific communication skills
- Willingness to collaborate and ability to work successfully in a team environment
- Experience in collecting and analyzing open-source spatial data to analyze land use and land cover change.
Available Position 3 = Remote Sensing Data Scientist
Description:
We are looking for an expert in machine learning to help us extract value from remote sensing data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.
The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field.
Responsibilities:
- Mines, retrieves, and applies statistical and mathematical analyses to spatial and non-spatial data from internal and external databases to identify trends, solve analytical problems, derive insights, and inform decision-makers. Develops testing frameworks and tests of database and models quality and performance.
- Identifies and collects data from various sources and evaluates and assesses its accuracy and effectiveness; prepares data for efficient analyses.
- Apply remote sensing data or techniques, such as surface water modeling or dust cloud detection, to address environmental issues.
- Develop automated routines to correct for the presence of image distorting artifacts, such as ground vegetation.
- Performs exploratory data analysis, visualizes information using existing and new tools (ArcGIS, QGIS,R, Excel, etc.), develops scripts and algorithms, creates explanatory and predictive models, and conducts comparative analyses to addresses specific problems and questions.
- Performs difficult technical research and project development related to complex GIS and data analysis related problems. Evaluates alternatives and recommend effective courses of action. Serves as a technical resource on difficult technical issues. Prepares and maintains technical documentation and accurate, organized records.
Requirements:
- Strong proficiency with imagery, geospatial, or other high dimensional data such as hyperspectral imagery, multispectral imagery, remote sensing, and large-scale cloud computing
- Strong proficiency in predictive modeling to include comprehension of theory, modeling/identification strategies and limitations and pitfalls, implementing deep learning architectures for image classification, object detection, and object segmentation, or working with high dimensional data space, including image, weather, and genomic data
- Experience in conducting large-scale data analysis through all project phases and entire project lifecycles (understanding business requirements, project definition, formulating analytical approaches, performing data development, extraction, and exploration, statistical analyses and algorithm development and testing, and interpreting and presenting findings and results).