Predictive Analytics Spring Co-op – #01CW5
If you love developing innovative, breakthrough technologies that create breakthrough products, you???ll want to check out this exciting Data Science & Analytics opportunity at Monsanto. Produce more. Conserve more. Improve lives. That???s Monsanto???s vision for a better world. Achieving this vision demands revolutionizing agriculture through technology. Agriculture adoption of GPS, sensors, imaging and state-of-the art precision equipment has enabled the creation of computer generated prescriptions for farmers??? fields. The ag transformation from simple, mechanical based operations to complex computer based systems is possible because of data science & analytics. The digital revolution in agriculture rivals past technology changes such as mechanization, hybrid seeds, and biotechnology. There???s never been a greater demand for your skills in agriculture. So why choose Monsanto? We are seeking an exceptionally talented graduate-level student who shares our passion for innovation to be part of our Global Analytics Team at our world headquarters in St. Louis, Missouri. This team has access to data you???ve only dreamt about and is driving creation of predictive, prescriptive models that will shape the industry. We work on hard problems because we love the challenge. As part of our diverse, highly dynamic group, you will work side-by-side with a team of exceptional data scientists with diverse backgrounds (Geneticist, Mathematicians, Statisticians and Engineers) to foster your career growth and development while delivering next-generation scientific breakthroughs. The Predictive Analytics Co-op will develop predictive models and decision support tools to optimize Monsanto???s product testing and commercial deployment platforms, and support Monsanto???s shift to Digital Ag by developing novel yield zone based predictive approaches with multiple heterogeneous data (e.g., geospatial data including soil physical and chemical properties, remote sensing, crop yield and weather). A key area of focus will be to conduct genomic and phenotypic analysis and improve genomic-assisted selection in row crops. In addition, you will learn the decision-making process in Monsanto???s product development pipeline, to gain experience of implementing predictive analytics model in the Ag industry. Dates for this spring co-op are January 2 – June 16 of 2017. Qualifications:Required:Candidates must be currently enrolled in a Masters or PhD degree program in Statistics, Statistical Genetics, Bioinformatics, Computational Biology, Plant/Animal Breeding or a related discipline Excellent background in statistics, and/or machine learning, and/or quantitative genomics/population genetics and have general knowledge of plant/animal breedingDemonstrated programming skills in R, Python, or other scientific programming language Preferred:Ability to solve challenging and complex analytical problems, and willingness to extend own statistical and mathematical interests into new fields of research and development Excellent entrepreneurial thinking, innovation, and real world problem solving skills Strong communication skills for effective interactions with senior business/R&D stakeholders as well as peer groups and team members Background in big data technologies including Apache Hadoop, Spark and IaaS such as AWS and Google Cloud is highly desirableApply for this job.