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Lead Data ScientistBayer Global • United States
Postuler Maintenant
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Lead Data Scientist

Bayer Global
  • US
    United States
  • US
    United States
Postuler Maintenant

À propos

Lead Data Scientist
Lead agronomic data science research projects for development and deployment of crop placement models; design and prototype agronomic models; define research problems and develop strategic planning for agronomic data science projects; mentor and provide feedback to junior team members on model development and validation; construct data-driven evaluation frameworks and communicate modeling results to technical and non-technical stakeholders; lead the design and statistical analysis of field trial protocols. Requires Master's Degree in Data Science, Customer Analytics or closely related quantitative field and 5 yrs professional agronomic industry experience developing data collection pipelines for agronomic and environmental datasets using SQL, PySpark and Google BigQuery; performing exploratory data analysis of agronomic data to evaluate data quality and data trends using Matplotlib and Seaborn; building machine learning and deep learning models in Python for agronomic predictions, using Keras, Tensorflow, Sklearn and XGboost; creating and deploying CI/CD pipelines with Artifactory; performing code documentation, unit testing and code modularization; using GitLab to track code history and perform code review; and designing and analyzing agronomic trial data, including experimental protocols and hypothesis testing. Up to 5% U.S. and int'l travel req'd. Telecommuting permitted up to 2 days per wk from home office location within reasonable commuting distance of St. Louis, MO. Salary Range: Employees can expect to be paid a salary between $140,000.00 to $175,000.00. 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.
  • United States

Compétences linguistiques

  • English
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