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Your Tasks and Responsibilities

• Independently develop algorithms in R and/or Python to clean, process, analyze and visualize large multivariate datasets (genotypic, environmental, and phenotypic);
• Work closely with data science team and business partners to break down complex business problems to build feasible solutions that are impactful, accurate and validated;
• Design and prototype models using machine learning, statistical modeling, process modeling, and other techniques such as machine learning;
• Work with mentor and other researchers and scientists to quickly gain domain knowledge and understand business processes;
• Present data driven insight, recommendations, and solutions to a broad range of audiences including peers, leadership and internal customers in a clear, interpretable manner;
• Expand professional networks with the business and the Data and Data Science Community

Required Qualifications

• Pursuing Ph.D. (or M.S. final year) in a discipline related to Data Science (e.g., Statistics, Mathematics, Computer Science/Engineering);
• Theoretical knowledge and practical experience with advanced statistical and machine learning modeling techniques;
• Strong desire to develop a career in Data Science;
• Fluency in using SQL, Python or R for data manipulation, computational statistics, and model development;
• Knowledge and experience in modeling environmental and crop phenology data;
• Strong communication skills and the ability to work with diverse cross-functional teams;
• Ability to turn complex biological or engineering data into meaningful insights;
• Execute responsibilities with knowledge, integrity, commitment, and excellence

Preferred Qualifications

• Experience with mixed effects regression, clustering, outlier detection, survival analysis modeling
• Technical experience working with Github, Google BigQuery, and Markdown Terms
• Project Duration: at least six months
• Expectation: 40 hrs/week

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