Agoro Carbon Alliance
Senior Data Scientist – Soil Carbon Modelling
About the job
We are reducing agriculture’s global greenhouse gas emissions to improve the world we live in!
Agoro Carbon Alliance addresses a key global problem; the impact of agriculture’s global greenhouse gas emissions on our climate and the implementation of sustainable carbon capturing potential at farm. Our passion lies in solving this global crisis by working with our customers and partners to bring about sustainable transformation of farming practices incentivised by making this economically viable for the grower.
A Bit About The Role
Our team brings together knowledge in (geo-)statistics; agriculture, soil and carbon science; as well as applied data science to support Agoro’s monitoring, reporting and verification (MRV) process of greenhouse gas emissions – with a primary focus on soil carbon sequestration.
As a Senior Data Scientist Within Our Carbon Science And Analytics Team, You Will Contribute To The Development Of Robust Carbon Modelling Approaches, In The Context Of The Design And Implementation Of
- stratification approaches, for physical soil sampling purposes
- a cost-effective monitoring approach of soil organic carbon (SOC) stock, resulting from various sustainable management practices
Your work will drive several aspects of Agoro’s core business, for instance:
- Assess soil sequestration potential and prioritize areas for business development
- Optimize carbon credit claims, by ensuring robustness and traceability of the “carbon journey”
- Decrease the cost of SOC quantification by the innovative combination of different approaches
You will combine your expertise in deploying existing carbon models such as Century/DayCent, RothC, DNDC, etc. with the use of other approaches, gradually including remote and proximal sensing data for carbon monitoring. To do that, you will work closely with a remote sensing expert.
You will be expected to leverage a wide range of datasets, going all the way from global climate data, to local farm/field data. Your models will span across various ranges of spatial, temporal and spectral resolution. You’ll be expected to handle these independently, and with great ease.
Carbon crediting resulting from the implementation of sustainable management practices in farms, evolves in a rapidly changing “regulatory” framework. Your agility and eagerness to continuously suggest and develop innovative ideas will therefore be an important feature of your profile.
You will be working with our data engineering team to build your prototypes to production and running on scale.
What You Will Be Doing
- Work closely with business stakeholders to identify value and business needs related to soil carbon modeling and translate them into concrete data science problem statements
- Work closely with our agronomy, product, data science and engineering teams to build perational, state of the art soil carbon monitoring systems
- Bring academic research, technology and practical experience together to drive Agoro’s soil modeling strategy forward
- Rapidly prototype and iterate to build production ready solutions that scale
- Identify and build the right user experience so that the output of your ML workflows is easily interpretable and actionable by the business users
- Tune your models efficiently and write clean and interpretable code
- Execute a variety of business critical initiatives driven by our Solution teams through developing, testing and implementing data analytics and algorithmic solutions
- Participate in the full life cycle of solutions, from early stage rapid prototyping through to scaled implementation and continuous improvement after initial launch
- Contribute in education and evangelization of applied data sciences and geostatistics throughout the business
What You Will Bring
- MS/PhD in Agriculture/Environmental/Soil Science, or Computer science, Machine Learning, Applied Math, Statistics, Physics, or similar
- Min 5 years of experience in applied data science, analytics or similar role, working on soil carbon modeling systems
- Expertise in working with relevant soil carbon models (e.g., Century/RothC/DNDC) is critical
- Preferred experience in the design of sampling campaigns and monitoring networks (incl. the development of methodologies for the sampling design, stratification, soil sampling and lab analyses protocols)
- Experience with remote and proximal sensing datasets is a plus
- Highly proficient and experienced in scripting languages such as Python and R, statistical and modelling packages, and rapid prototyping, with ability to write clean, sharable and efficient code
- Solving hard (geo-)statistical modelling and machine learning problems truly excites you. To do this, you are constantly stretching your toolbox of capabilities, including breaking new ground when required.
- You are an effective communicator of technical concepts to both technical and non-technical resources
- Pragmatic, solution driven and technology agnostic. You focus on results, and get things done.
- Prior agricultural experience is an advantage, especially in a commercial context
- We offer the opportunity to drive change by globally reducing carbon emissions while financially supporting growers.
- You would be working with a globally dispersed and diverse team. We adopt a virtual-first approach, where we encourage face-to-face collaboration, but are focused on recruiting the best talent.
- Support for personal development, learning and continuous learning is a priority.
As a global organization we actively strive to reflect the diversity in society. We therefore encourage all qualified applicants from all background to apply and are committed to creating a work environment that fits gender equality and allows combining career progress with the needs of a family or other personal circumstances.
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