At a Glance
- Tasks: Lead carbon monitoring and ensure high-quality forest measurement data.
- Company: Join Africa’s leading forest restoration company on a mission to restore degraded land.
- Benefits: Flexible hybrid/remote work, impactful projects, and the chance to make a difference.
- Other info: Dynamic role with opportunities for growth and innovation in ecological science.
- Why this job: Be at the forefront of forest restoration and combat climate change.
- Qualifications: PhD in relevant field, proficient in R/Python, and experience in tropical forests.
The predicted salary is between 60000 - 80000 £ per year.
Full-time (hybrid/remote) Up to 3 months/year at projects in West Africa
About Rainforest Builder
Rainforest Builder is Africa’s leading forest restoration company, on a mission to restore one million hectares of degraded land to tropical forest. We bring together world-leading science, forestry, and tech, to deliver high-quality forest restoration at unprecedented scale. Backed by some of the largest companies and investors in the world, we remove millions of tonnes of CO2 from the atmosphere, restore globally threatened biodiversity, and deliver equitable economic growth to rural communities. We currently operate four projects across three countries in West Africa and are continuing to expand to new areas within the region.
Role overview
As our Lead forest carbon scientist, you will be the driving force behind our programme of carbon monitoring, providing technical oversight and ensuring that we consistently deliver high-integrity forest measurement data through highly scalable, efficiently run field operations. To date, we have measured over 150 ha of degraded tropical forests, a number set to double again over the next two years. Ensuring that we consistently apply the same high standard of implementation across a large, and growing, field operation requires an individual who cares about detail, has excellent data handling ability, and a deep knowledge of tropical forests and the realities of working in them. In this role, you will provide quality assurance for all of our carbon monitoring processes and data outputs, and lead on bringing new technologies to bear on our measurements and carbon accounting.
The ideal candidate will:
- have excellent data handling and analytical skills, with experience working with complex ecological data
- have a depth of experience in the field of tropical forest ecology, and understand how leading carbon methodologies (e.g. VM0047) account for forest carbon change
- be highly self-motivated and can operate with high agency to identify and manage problems effectively
Key Responsibilities
- Continually assess and improve our forest carbon measurement protocols, ensuring that they keep pace with scientific developments and remain at the leading edge of measurement standards
- Oversee implementation of our measurement protocols across a large field-monitoring operation consisting of many teams spread across multiple countries.
- Own our carbon data: data management, identify and investigate data errors and inconsistencies; work with field teams to address root causes, and continually refine our processes
- Contribute to the development of tools and processing pipelines to handle and manage carbon data
- Integrate remote sensing (satellite and drone), and LiDAR into the monitoring framework.
Candidate requirements
- PhD in a relevant field
- Proficient in R and/or Python
- Comfortable handling complex ecological datasets: identifying anomalies, tracing errors, and building reproducible analytical workflows
- Able to construct appropriate statistical models to answer questions and deliver insights, and produce clear data visualisations and data summaries as required
- Experience working in tropical forests. You do not need to be a carbon accounting specialist, but you should understand enough forest ecology sufficient to interpret monitoring data critically, and some knowledge of leading accounting methodologies is a plus.
- Experience with remote sensing datasets, drone imagery, or LiDAR in a forest monitoring or ecological research context
- Highly self-motivated, and excited by the challenge of maintaining scientific rigour across a large field operation.
- Excellent problem solver- able to identify problems and challenges as they emerge and resolve appropriately
To apply
Please email with a CV and covering letter, including the job title in the subject line. Applications via LinkedIn will not be reviewed.
Lead forest carbon scientist in Portsmouth employer: Rainforest Builder
At Rainforest Builder, we pride ourselves on being a leading employer in the field of forest restoration, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through our support for continuous learning and development, particularly in the unique context of West Africa where you will have the opportunity to make a tangible impact on biodiversity and local communities. Join us in our mission to restore degraded lands while enjoying the flexibility of a hybrid work environment and the chance to work with cutting-edge technologies in a meaningful role.
StudySmarter Expert Advice🤫
We think this is how you could land Lead forest carbon scientist in Portsmouth
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend relevant events, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a presentation that highlights your experience with carbon monitoring and data handling. This will give you an edge during interviews and show that you're serious about the role.
✨Tip Number 3
Practice makes perfect! Conduct mock interviews with friends or mentors to refine your answers and get comfortable discussing your expertise in tropical forest ecology and data analysis.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our mission at Rainforest Builder.
We think you need these skills to ace Lead forest carbon scientist in Portsmouth
Some tips for your application 🫡
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Make sure to highlight your experience in tropical forest ecology and data handling. Show us how your skills align with our mission at Rainforest Builder.
Tailor Your CV:Don’t just send the same CV for every application. Tailor it to reflect your relevant experience and skills that match the Lead Forest Carbon Scientist role. We want to see how you can contribute to our projects!
Showcase Your Technical Skills:Since we’re looking for someone proficient in R and/or Python, make sure to include specific examples of how you've used these tools in your previous work. We love seeing practical applications of your skills!
Follow Application Instructions:Make sure to apply through our website as instructed. Include the job title in the subject line of your email. Following directions shows us you pay attention to detail, which is super important for this role!
How to prepare for a job interview at Rainforest Builder
✨Know Your Carbon Science
Make sure you brush up on your knowledge of carbon methodologies, especially VM0047. Be ready to discuss how these methodologies apply to forest carbon change and how you can contribute to improving measurement protocols.
✨Showcase Your Data Skills
Prepare to demonstrate your proficiency in R and/or Python. Bring examples of complex ecological datasets you've worked with, and be ready to explain how you identified anomalies and built analytical workflows.
✨Field Experience Matters
Since this role involves working in tropical forests, share your field experiences. Talk about the challenges you've faced and how you've overcome them, as well as any technologies like remote sensing or LiDAR that you've used.
✨Problem-Solving Mindset
Be prepared to discuss specific problems you've encountered in previous roles and how you resolved them. Highlight your self-motivation and ability to operate independently while maintaining scientific rigour across operations.