Carbon Modeler
1 week ago
About Olam Agri
Olam supplies food, feed, and fibre to meet rising demand and a shift to protein-based diets, particularly in Asian and African countries. Headquartered in Singapore and present on all continents, our value chains include farming, processing, and distribution operations, as well as a sourcing network of an estimated 2.5 million farmers. Our teams have built leadership positions in many OGA businesses, which include rice, flour, animal feed, sesame, cotton, wood, and more. As a purpose-driven company, we aim to contribute positively to the prosperity and well-being of people along our supply chains, protect and regenerate our natural resource base, and the fight against climate change.
Role Overview
- Apply models to quantify carbon avoided or removed in the context of wide-ranging emission reduction projects within the own estates and supply chains
- Use data analytics as required by carbon methodologies to calibrate and validate mechanistic and empirical models, estimate uncertainty in C estimations etc.
- Collaborate with the climate action manager in designing projects to acquire accurate data for projects covering e.g. climate, water, soils, energy use, full life cycle of agri crops in a broad range of products and production systems as well as geographic origins.
- Support other members of Environmental team with research and analysis of farm-level and landscape-level data (ex. yield, carbon, biodiversity, water) in key production origins
- Identify inconsistencies with data and resolve issues, documenting the learning process.
- Support the development of visual materials that illustrate findings and results from large amounts of data in the form of presentations and reports.
- Staying abreast of trends and best practices in data mining and analytics, impact metrics and GIS, especially with applications for sustainable agriculture, monitoring land use change, and assessing social impact repetition.
Qualifications
- Master's or equivalent experience in data analytics, statistics, environmental anaytics, data science or equivalent quantitative research experience if she/he has a different academic background
- A personal passion for sustainable agriculture and food systems
- Demonstrated ability to work with large volumes of data
- Excellent analytical skills and advanced competency in Microsoft Excel, R, Python, etc.
- An understanding of different carbon and other environmental standards especially related to land use sector.
- Ability to work closely with other data analysts, collaborating on data needs and acquisition
- Understanding of Machine Learning frameworks, tools, and algorithms are desirable
- Strong leadership and interpersonal skills, with a proactive, solution-oriented and innovative mindset
- Critical thinking skills, organizational skills, and the ability to design and manage programmes.
- On-the-ground experience and a good understanding of agri-business models and success factors are highly desirable
- Willing to occasionally travel to remote operational areas
- 4-6+ years of relevant professional experience
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