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Data Scientist

Seattle, WA, United States

Climate LLC: Data Scientist for Seattle, WA to build, prototype & test predictive agronomic models to address scientific challenges in precision agriculture; explore, analyze & munge complex agronomic datasets; apply machine learning, process modeling & statistical modeling techniques for model development; write research code & libraries; collaborate with scientists, engineers & mathematicians to deliver research findings. Requires Master’s in Data Science, Machine Learning, Computer Engineering, Computational or Computer Science, or a closely-related quantitative field & 2 years of experience building predictive machine learning & statistical models for research applications; writing code in Python with data science packages, including Numpy, Pandas, Matplotlib, Seaborn & Sklearn; conducting exploratory data analysis to evaluate data trends; working with large, complex datasets using SQL & PySpark; using version control systems, including Git, to track code history; joining large & diverse datasets across multiple databases and performing data quality checks; and communicating with technical & non-technical stakeholders at all levels of the organization, including business and/or academic stakeholders, peer groups and team members. Telecommuting permitted from home office location within reasonable commuting distance of Seattle, WA up to4 days per week.Salary Range:  Employees can expect to be paid a salary between $155,000.00 to $180,000.00.  Additional compensation may include a bonus or commission (if relevant).  Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc. The offered salary may vary within this range based on an applicant’s location, market data/ranges, an applicant’s skills and prior relevant experience, certain degrees and certifications, and other relevant factors.Mail resume to Jill Martin, Climate LLC, 4 City Place Drive, Suite 100, St. Louis, MO 63141 or email resume to [email protected]. Reference Job Code 3550.

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