Data Scientist Agronomy & Remote Sensing Job in Bayer

Position Purpose:
At Bayer, we are committed to solving the world s most challenging problems, including revolutionizing farming practices. We are seeking a Data Scientist - Agronomy & Remote Sensing to lead the development of data-driven agricultural solutions. By combining expertise in soil science, crop modeling, remote sensing, and advanced analytics, you will create innovative digital products that enhance agricultural productivity and improve farming practices.

Key Responsibilities

• Innovation & Experimentation: Collaborate with cross-functional teams to build data-driven solutions and offerings for farmers.
• Model Development: Develop weather and climate change models using statistical and process-based methods.
• Field Experiments: Design and lead field experiments, guiding field officers for data collection and model validation.
• Predictive Modeling: Build predictive models to map soil properties and field variabilities using statistical and modeling techniques.
• Collaboration: Work with data scientists and engineers to develop models that diagnose, predict, and analyze crop performance.
• Deployment: Deploy analysis results and models into customer-facing services, monitor performance, and improve models.
• Data Handling: Clean, analyze, and visualize complex agricultural, remote sensing, and geospatial datasets to derive actionable insights.
• Data Quality: Work with the data quality team to resolve any data-related issues.

Who You Are

• Educational Qualification:
  • MS with 5+ years of experience in soil research and remote sensing, or
  • Ph.D. in Remote Sensing, Soil Science, Agronomy, Environmental Science, or a related field.
• Experience:
  • Expertise in remote sensing, agricultural, and geospatial datasets, applying data science techniques to real-world problems.
  • Strong background in soil hydrology and/or Agronomy with experience in using geospatial datasets (e.g., SoilGrids, ERA5).
  • Proficiency in GIS software for geospatial analysis.
  • Experience with Python/R and SQL for data analysis.
  • Familiarity with statistical modeling techniques like Linear Regression, Partial Least Squares, Random Forest, Neural Networks, etc.

Why Bayer?

• Dynamic Shared Ownership (DSO): Bayer promotes a culture of productivity, innovation, and faster results, reshaping how we work together.
• Equal Opportunity Employer: Bayer values fairness, respect, and diversity, offering equal opportunities regardless of race, religion, gender, or other factors.