Data Science Lead at FarmTogether

Remote | High-paying
FarmTogether

Data Science Lead

  • San Francisco Bay Area • or Remote
  • $135k – $165k
  • Create a New Asset Class. Feed the Planet. Fight Climate Change.

FarmTogether is creating a technology-driven investment and trading platform for a brand new asset class – a $10 trillion global farmland market, previously only accessible to the largest institutional investors. This is a unique opportunity to join at the very beginning of this exciting journey and help grow a truly innovative financial product while also having an active role in battling climate change and creating food systems of the future.

We are looking for a hands-on Data Scientist Lead (US-based, ideally Bay Area) who can build out the Data Science function. In this role, you will use your full toolkit statistical modeling, machine learning, data mining, data visualization, and software engineering to develop data products and models that are used by internal teams to help us find, price, underwrite and manage farms.

DATA SCIENCE LEAD

Responsibilities

  • Work closely with Head of AI & Automation to design, test, refine and deploy Data Science models that help the Sourcing team find and underwrite farms that fit our investment theses.
  • Vet, select and deploy Data Science research and learning environment
  • Own the Data Science roadmap
  • Build the Data Science function
  • Champion a data-driven culture and push long-term business value creation through development of best-in-class Data Science capabilities.

Example Projects

  • Determine the optimal pricing strategies to help FarmTogether consistently win deals and maximize returns for our investors
  • Deploy large scale Machine Learning algorithms that power our farmland ranking models and portfolio fit engine
  • Develop, test and deploy a climate change risk / water supply risk model for each of our crops and geographies

Minimum Qualifications

  • A Bachelor’s/Master’s degree (or higher) in a technical field (Computer Science, Statistics, Economics, Operations Research, Math, Physics, Engineering, etc.) or equivalent work experience required.
  • A minimum of 3+ years of professional experience in Data Science or Applied Machine Learning required
  • A deep theoretical understanding of modern machine learning algorithms, statistical models, or optimization
  • Extensive experience with data tools, Python (Pandas, Scipy, Numpy, Scikit-Learn, etc), R, SAS, SQL, etc and strong skills in data analysis, data visualization, and feature engineering
  • Ability to own your modeling work from model development all the way to production deployment and beyond with minimal help from engineers
  • Strong communication skills; Explaining complex technical concepts to product managers, data analysts, and other engineers shouldn’t be a problem for you
  • Self-starter that is able to develop, plan, test and refine models with minimal supervision
  • Familiarity with climate, environmental, pricing and/or geospatial modeling
  • Experience working in a fast-growing startup environment

Preferred Qualifications

  • MS/PhD in Computer Science, Statistics or Data Science
  • Experience with ML frameworks like Tensorflow, PyTorch, Spark MLlib, XGBoost, and Scikit-Learn
  • Demonstrated ability to recruit, build and manage a team of Data Scientists

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