Monsanto Applied Statistician in ST. LOUIS, Missouri

Monsanto's Global Technology Development (TD) organization is seeking a highly motivated Applied Statistician to join our Data Science and Analytics team in North America. The successful candidate will be responsible for delivering cutting-edge analytical solutions and facilitating advancement of products and tools to provide integrated agronomic solutions to customers.

The Applied Statistician will provide insight and recommendations for key field trial designs and will also utilize statistical methodologies to conduct analyses of data from agronomic field research involving germplasm performance evaluation, and innovative crop management, crop protection, biotech and biological solutions. Data analyses will involve multi-layered agronomic, imagery, geo-spatial and environmental data (weather, soil attributes etc.,) utilizing advanced statistical and data modeling methodologies, predictive modeling and data mining techniques. The position will also contribute to the development of scalable data and analytical solutions to support the North America and Global TD business.

This is a dynamic role that requires cross functional collaboration with key internal stakeholders, including R&D, IT, Global Supply Chain, The Climate Corp., Marketing & Product Management, Sales, and Global Technology Development & Agronomy teams.

Key Responsibilities:

  • Provide statistical recommendations on experimental design, power analysis, and protocol development during the planning stages of field activities

  • Deliver analytical solutions using innovative statistical & data modeling methodologies for analyzing data in alignment with experimental protocols

  • Conduct analysis and deliver clear interpretation of trial results & reports to drive strategic decisions, knowledge transfer, and marketing/sales support as needed

  • Develop and implement analytical approaches/methodologies to effectively use spatially referenced multi-layered data to gain insight into the impact of agronomic and environmental factors on product performance and positioning

  • Contribute to development of predictive and scalable analytical tools for providing integrated agronomic solutions to growers collaborating with various stakeholders across company

  • Collaborate with Data Scientists and stakeholders to standardize tools/develop best practices for experimental planning and trial set up, data collection, analysis and data utilization globally

  • Actively engage Data Science colleagues within other Monsanto disciplines for collaboration and learning

Required Skills/Experience:

  • PhD or M.S. in statistics, mathematics, or other related quantitative or agronomic discipline, with at least 2 years of experience utilizing data management and analysis techniques

  • Experience with analytical tools such as R, SAS, Python, SQL, etc., and data modeling methodologies

  • Experience in data management, summarization and interpretation

  • Expertise in wide range of statistical techniques including, but not limited to experimental design, linear and non-linear mixed models, multivariate statistics, random forest, non-parametric analysis, and Bayesian statistics

  • Understanding of machine learning algorithms and building predictive models

  • Clear proficiency in presentation, communication and team coordination skills

  • Ability to work in a team environment collaboratively but function independently

  • Ability to prioritize and deliver across requests from multiple teams and individuals

Desired Skills/Experience:

  • Experience in both statistical analysis and agricultural field research with knowledge of key cropping systems

  • A basic understanding of agricultural practices and conducting on-farm experiments

  • Drive for continuous improvements and critical thinking which can be translated into research initiatives and reporting outputs that deliver business value

  • Experience with utilizing and modeling environmental data, including soils and weather data, especially for understanding genotypic interactions with environment

  • Strong foresight, planning, prioritization and organization skills

  • Works with a sense of urgency, identifies and overcomes obstacles, takes necessary risks; balancing big picture concerns with day-to-day activities

  • Ability to identify and satisfy the needs of internal customers and continuously search for ways to provide value-added solutions

  • Ability to lead and influence activities of cross-functional teams without direct reporting relationships

Organization: GLB TD Data Science & Analytics51180504_

Title: Applied Statistician

Location: North America-USA-Missouri-St. Louis

Requisition ID: 01JUI

Job: Product/Technology Development

Schedule: Full-time

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