Tech Lead Sustainability Data Science

Creve Coeur, Missouri, US

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At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

 

Tech Lead Sustainability Data Science 

 

Technical Lead, Sustainability Data Science

We're seeking a visionary Sustainability Data Science Director to spearhead our efforts in driving regenerative agriculture transformation. Leveraging advanced modelling, artificial intelligence techniques and interdisciplinary collaboration (DFS, R&D, StS), the incumbent will play a key role in developing comprehensive models that capture the complex interactions within regenerative agriculture metrics and outcomes.

 

YOUR TASKS AND RESPONSIBILITIES

 

The primary responsibilities of this role, Technical Lead, Sustainability Data Science, are to:

 

  • Lead and oversee the quantification and analysis of regenerative agriculture outcomes in agricultural systems and innovations;
  • Develop and implement advanced statistical models to analyze and interpret sustainability-related data, ensuring the utmost accuracy and reliability in regenerative agriculture assessments;
  • Drive the design and implementation of complex artificial intelligence algorithms to enhance precision farming techniques, particularly in the precision agriculture approach;
  • Develop and deploy algorithms in Python and/or R to clean, process, analyze, and visualize large multivariate environmental and agronomic datasets;
  • Collaborate closely with cross-functional teams, including SSE capability center, R&D, IT and DFS, to provide data-driven insights and recommendations for sustainability efforts;
  • Execute rigorous sensitivity analyses and model validations to ensure the highest standards of accuracy and reliability in regenerative agriculture assessments;
  • Pioneer the exploration and implementation of cutting-edge statistical and machine learning techniques to elevate model performance and predictive capacities within the organization;
  • Design, develop, and deploy deep learning models to interpret complex datasets and predict future environmental outcomes, enabling preemptive action in sustainability efforts;
  • Identify and develop user-friendly tools and applications for visualizing and communicating model outputs to stakeholders at all levels of the organization, empowering data-driven decision-making;
  • Stay at the forefront of environmental science and data analytics, incorporating the latest research findings into model development to enhance the efficacy of sustainability assessments and drive novel solutions for regenerative agriculture.

WHO YOU ARE

 

Bayer seeks an incumbent who possesses the following:

 

Required Qualifications:

 

  • A Master's or -preferably- Ph.D. in a relevant field such as Computer Science, Environmental Science, Agronomy, Ecology, or Biotechnology or related field or equivalent combination of education and experience;
  • Significant experience in sustainability data science, focusing on agricultural systems, soil health, and carbon sequestration;
  • Proficiency in advanced statistical analysis, machine learning techniques, and data visualization tools, with fluency in Python or R;
  • Sound knowledge of theoretical and applied statistics, including experimental design, multivariate analysis, and decision trees;
  • Experience in developing and applying mechanistic process-based models to quantify ecosystem services and assess their impacts on soil health and carbon sequestration;
  • Proven ability to collaborate effectively with interdisciplinary teams and translate complex technical concepts into actionable insights for diverse stakeholders;
  • Strong leadership qualities with the ability to inspire and motivate teams towards common goals, drive innovation, and lead organizational change towards sustainability;
  • Demonstrated experience in project management, including planning, execution, and evaluation of sustainability data science projects within tight timelines and budgets;
  • Excellent communication skills for presenting findings to both technical and non-technical audiences;
  • Genuine passion for sustainability and a deep commitment to driving positive environmental impact through data-driven approaches in the food and agriculture sector.
    YOUR APPLICATION      

Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Science for a better life, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer. 
To all recruitment agencies: Bayer does not accept unsolicited third party resumes.
 
Bayer is an Equal Opportunity Employer/Disabled/Veterans
 
Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below. 

 

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.

 

 

  Bayer is an E-Verify Employer.             Location: United States : Missouri : Creve Coeur      Division: Crop Science     Reference Code: 820404          Contact Us     Email: hrop_usa@bayer.com
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Tags: Computer Science Data Analytics Data visualization Deep Learning Machine Learning ML models Python R R&D Research Statistics

Perks/benefits: Career development Competitive pay Health care

Region: North America
Country: United States

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