Data Scientist - Intermediate
San Francisco, CA
$76,936 - $142,012 (Glassdoor Est.)
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Rating Highlights
Compensation & Benefits: 4.1
Culture & Values: 4.1
Career Opportunities: 3.6
Work/Life Balance: 4.1
Job & Company Insights
Job Type: Full-time
Job Function: data scientist
Industry: Biotech & Pharmaceutical
Size: 10000+ Employees

The Yield Modeling team at The Climate Corporation is looking for a highly motivated researcher with applied experience in data science and deep learning. The position is within the science R&D team that leverages modeling, big data, and cloud computing to address scientific challenges in precision agriculture. As a member of the Yield Modeling team, you will use state-of-the-art statistical, machine and deep learning models to tackle hard problems related to predicting and understanding variation in crop yield using industry-leading data sources.

What You Will Do:

  • Explore and munge large and diverse agronomic datasets to gain insight and build model-ready datasets
  • Design, prototype, and validate predictive agronomic models using machine/deep learning and statistical models
  • Write robust, well-documented and well-tested research code and code libraries that adhere to community standards and best practices
  • Collaborate with team members and across the Science organization to deliver high-quality, reproducible research

Basic Qualifications:

  • PhD or MS with 2 years of experience in Computer Science, Data Science, Statistics, Applied Math or another highly quantitative discipline
  • Strong Python coding skills for data science, including experience with standard data science packages (numpy, pandas, matplotlib, seaborn, sklearn)
  • Experience using version control systems (preferably git) and cloud computing (preferable AWS)
  • Strong communication skills for effective interactions with business stakeholders as well as peer groups and team members

Preferred Qualifications:

  • Hands-on deep learning and statistical/probabilistic modeling experience
  • Experience using probabilistic programming languages, such as Tensorflow Probability and Pyro
  • Experience with exploratory Big Data discovery through the use of technologies such as Spark (PySpark preferred)
  • Knowledge of agricultural technology especially with regard to row crops
  • Curiosity and an open-mind towards unfamiliar data sources and unfamiliar quantitative domains


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