Bayer is looking to solve critical problems and answer important questions that drive key decisions for their Plant Breeding business by leveraging remote sensing data and developing next-generation AI methodologies and models.
Requirements
- Intermediate proficiency in computational skills and level of experience building data models using Python, R or other programming packages, including CV/ML libraries and deep learning frameworks such as PyTorch
- Basic understanding of software development best practices (Version Control, Code Documentation & Review)
- Proficiency using Python
- Strong proficiency with geospatial and imagery data such as geophysical soil sensing, remote sensing, hyperspectral, multispectral imagery, open source geospatial technologies and large-scale cloud computing
- Strong proficiency in predictive modeling to include comprehension of theory, modeling/identification strategies and limitations and pitfalls
- Experience in the successful delivery of valuable analysis through the application of domain knowledge; evidence of ability to strong business acumen
- Experience with technologies such as: Diffusion, Latent Diffusion Models, Text-to-image synthesis, Image inpainting, Super-resolution, and Flow Matching
Responsibilities
- Lead the efforts to create breakthroughs in precision plant breeding by exploring and developing the next generation of satellite enabled AI methodologies and models
- Leverage recent advances in high resolution remote sensing and IoT sensors to develop models that predict novel phenotypes
- Acquire, process, transform, and extract information from high resolution remote sensing imagery
- Create innovative insights from imagery and sensor data with a focus on large scale geo-temporal analyses, computer vision and remote sensing, feature extraction from imagery and time series data, crafting complex model architectures using embeddings and ML/DL techniques
- Independently perform computer programming, predictive modeling, statistical analysis, and experimental design using advanced mathematical models, machine learning algorithms, and strong business acumen to deliver insights, recommendations, and solutions
- Develop sustainable, consumable, accurate, and impactful reporting on model inputs, model outputs, observed outputs, business impact, and key performance indicators
- Present compelling, validated stories to all levels of organization, including peers, senior management, and internal customers to drive both strategic and operational changes in business.
Other
- Master’s degree in relevant technical field with at least two years of experience OR PhD with strong educational preparation and some applied experience
- Educational preparation or applied experience in at least one of the following areas: Geographical Information Systems, Machine Learning, Electrical/Industrial Engineering, Operation Research, Biostatistics, Computational Biology, Applied Mathematics, Generative AI, Computer Science and/or other related quantitative discipline
- Strong communication competencies to include presentations and delivery of complex quantitative analyses in a clear, concise, and actionable manner to the extended team and small groups of key stakeholders
- Build cross-functional relationships to partner with the business collaboratively and effectively network within the Data Science Community
- Collaborate regularly, acquiring support and partnership from cross-functional scientific, engineering, and IT teams across the company
