YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role, Vegetable Predictive Breeding Lead, are to: 

• Work with Breeding, Data Engineers, and technical leadership to solve data analysis challenges, create visualizations, enable higher levels of analysis and automation;
• Pilot advanced analytics methods, communicate their effectiveness, enable their deployment, and promote their adoption;
• Explore modeling solutions to accommodate large datasets in genomic prediction and optimize genomic prediction accuracy;
• Develop tools and applications that drive data informed decisions across the pipeline;
• Drive excellent IT and analytics citizenship by advocating good practices in local development which support the larger strategy for the digital transformation of Ag.
   

WHO YOU ARE

Your success will be driven by your demonstration of our LIFE values. More specifically related to this position, Bayer seeks an incumbent who possesses the following:

Required Qualifications:

• Bachelor’s degree with at least 12 years of experience in Animal or Plant Breeding, Quantitative Genetics, Data Science, Statistics, Biostatistics, Mathematics or Physics OR Master’s degree with at least eight years of experience OR Ph.D. with at least five years of experience;
• At least two years of experience developing and applying genomic prediction models to breeding and selection targets;
• At least three years of experience in any numeric computing such as BLAS/LAPACK, distributed computing, GPU computing or CUDA;
• Demonstrated passion and success in pursuing advanced statistical problems with complex data sets and experience programming in R, Python or Julia;
• Knowledge of genomic predictions and breeding theory and methods;
• Ability to develop both technical abilities and leadership in people through coaching and identifying key development opportunities;
• Strong theoretical and computational statistics skills;
• Demonstrated ability to work in cross-functional environment;
• Excellent analytics and software development practice;
• Ability and desire to coach and learn from other excellent practitioners;
• Ability to distill complex problems from Research and Development and Breeding subject matter experts and produce automated tools for complex and routine tasks;
• Understanding of modern machine learning techniques, their application to genomic prediction, and their mathematical foundation;
• Experience with machine learning packages such as TensorFlow or PyTorch and ability to customize for business needs;
• Excellent interpersonal and communication skills;
• Strong drive to learn new topics and skills.