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.

Data Scientist 

YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role, Date Scientist, are to:    

• Delivering predictive- and prescriptive models using machine learning, deep learning, and other technologies, fostering new game- changing ideas to produce sophisticated, intelligent optimization solutions and predictive models.
• Working as an individual contributor with other data scientists, data engineers and domain experts across the organization to solve critical problems.
• Independently performing computer programing, modeling and study design to drive the best quality of data science solutions.
• Creating data science solutions using advanced mathematical models, machine learning algorithms, operational research techniques and strong business acumen to deliver insight and recommendation for breeding pipeline decision. - Build cross-functional relationships to collaboratively partner with the business and effectively network within the data science community. - Demonstrating abilities to deliver presentations to broad audiences across functions.

Bayer seeks an incumbent who possesses the following:

Required Qualifications:

• Bachelor’s degree or applied experience in at least one of the following areas: Machine Learning, Electrical/Industrial Engineering, Operation Research, Statistical Genetics, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology, Applied Mathematics, Computer Science, or other related quantitative discipline.
• Expert level of proficiency in computational skills, including a deep understanding of advanced analytics techniques and emerging forms of analytics.
• Strong level of experience building data models using R, Python or other statistical and/or mathematical programming packages.
• Expert level of proficiency in Machine learning algorithms and concepts.
• Professional expertise in competencies in linear modeling, scientific modeling, and development and application of increased domain knowledge; proficiency in standard suite and/or modeling theories.
• Extensive experience in successful delivery of valuable analysis through application of domain knowledge; evidence of strong business acumen.
• Excellent communication skills with the ability to communicate complex analysis in a clear, precise, and actionable manner and deliver presentations to large audiences.

 Preferred Qualifications:

• Master’s or PhD degree in at least one of the following areas: Machine Learning, Electrical/Industrial Engineering, Operation Research, Statistical Genetics, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology, Applied Mathematics, Computer Science or other related quantitative discipline.
• Experience with SQL.
• Familiarity with Docker and CI/CD tools.
• Familiarity with advanced data science topics like Autoencoder, numerical optimization, transfer learning etc.
• Experience with cloud data science environments like Domino Data Lab and AWS Sagemaker.
• Experience with AWS, docker and other cloud deployment tools.
• Knowledge of plant breeding and/or plant biology.

To apply please click on APPLY TO THIS POSITION