Data Scientist - Natural Resource Econometrics

Location: San Francisco, CA

*** Mention DataYoshi when applying ***

About SilviaTerra
SilviaTerra helps mission-driven companies buy carbon credits from American forest owners. Based on a decade of work with America's largest landowners, our data-driven platform brings gigatons of new carbon offsets to market. Our mission is to work with every forest owner to unlock the full value of every acre.

Read more in this TechCrunch feature article about SilviaTerra.

We are backed by some of the world’s leading VC firms who were early investors in companies like Twitter, Etsy, Kickstarter, and Coinbase. Our global team of foresters, scientists, and technologists hails from leading research institutions and high growth technology startups.

We are looking for passionate, collaborative, and entrepreneurial individuals to join the team. If you like fast-paced environments and want to help us build the future of forestry, then we’d love to speak to you!

Job Description
SilviaTerra is built on terabytes of geospatial data, and we are rapidly expanding to integrate new types and structure of data into our work. Our Basemap dataset is our flagship data product- a high-resolution dataset of estimated number, species and size of trees across the continental United States. Basemap and its derivative metrics are critical components that underpin transactions on our carbon market.

This role is an integral part of that work, primarily responsible for improving and extending spatially explicit forecasts of annual forest change and harvest likelihood. The initial focus of this work is North America, with planned expansion globally. The Data Scientist - Econometrician will work closely with the rest of our team of forest biometricians and data scientists.

Our ideal candidate has familiarity with timber economics, experience with landscape-scale forecasting of behavior and change, and is eager to do applied work with real-world impact. If that's you, we want to meet you!

This is a remote position.

Key Responsibilities

  • Take the lead on improving and extending baseline disturbance-risk data products to inform high-resolution, spatially explicit estimates of available carbon for marketplace transactions
  • Research and understand current academic and commercial best-practices for forest disturbance modeling to inform model development
  • Evaluate relevant data sources and predictive techniques for answering critical questions about forest disturbance and landscape change. This may include economic models of behavior, ‘naive’ spatial data analyses, novel model design and/or adaptation of existing models (academic, commercial, or otherwise)
  • Develop methods for incorporating additional spatial data to benchmark and improve disturbance-risk data products
  • Assess, improve, and communicate the accuracy and precision of these models to stakeholders including internal and external parties (e.g., 3rd-party certification and verification bodies
  • Work closely with other members of the Data Science teams at SilviaTerra to ensure our modeling and data collection efforts are optimized for the improvement of forest disturbance modeling

Required Skills & Experience

  • PhD in Economics, Econometrics, Ecology, Forest Science, or a related field OR a Masters degree and 3 years of relevant work experience
  • Demonstrated ability to integrate large, disparate datasets for applied econometric analyses or forecasting
  • Demonstrated understanding of spatially explicit, large-scale work
  • Deep understanding of and applied experience using a variety of machine learning and statistical techniques
  • Familiarity with natural resource management and ecology
  • Fluent ability in Python or R (preferably both)

Desired Skills & Experience

  • Experience with time series and spatial modeling techniques
  • Familiarity with forest inventory, management, and ecology data
  • Familiarity with remote sensing
  • Experience with geospatial and remote sensing analyses using open-source software (QGIS, R and Python packages)
  • Detail-oriented
  • Excellent written communication skills
  • Comfortable working remotely with necessary travel for company meetings
SilviaTerra is an equal opportunity employer and will not discriminate against any employee or applicant on the basis of age, color, disability, gender, national origin, race, religion, sexual orientation, veteran status, or any classification protected by federal, state, or local law. Applicants must be authorized to work in the United States.

*** Mention DataYoshi when applying ***

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