Data Analyst – #01BS6

Monsanto is the world???s leader in developing sustainable agriculture systems that improve farm productivity, and minimize environmental impact for our planet???s growing population. As part of this mission, the Global Breeding Analytics team is seeking a Pipeline Metrics Analyst to join us in building a better understanding of the breeding pipeline, allow senior leadership to monitor our business in real time, and communicate complex predictive analytics.The position offers the opportunity to work with state-of-the-art data, experimental techniques, and analytical platforms.  In this role you will have ample opportunities to lead in-depth analyses on critical processes, design performance metrics and forecast outcomes, and proactively assess alternative solutions to under-performing indicatorsThe new hire will have primary responsibilities for collaborating with industry-leading domain experts and data science professionals with diverse backgrounds (eg. statistics, machine learning, operation research) across our R&D organization to develop the next generation of analytics; the goals of which are to improve product deployment and provide insights on their performance for improving the worlds best crop genetics. Responsibilities:Works with Stakeholders to define requirements, gather data and evaluate the need for new metrics or for improvements on existing metricsSurvey the state of both the relevant statistics in use and the availability of relevant data to have a clear and realistic concept for how to build/modify a metric that will help inform the decision-making processDefine and perform all the required tests to validate metric performance Identify data that needs to be collected that can add significant value to the decision-making process, as well as the feasibility of collecting the data and potential methods for working around missing dataDevelop, maintain, and document statistical code required for analysis, research and implementation of new statistical methodologies.Provide the proper evidence and context for a metric in order to demonstrate its value to the decision makerAdvises on opportunities for implementing consistency and standardization of metric identification, collection techniques and process improvement across crops and regionsManage and undertake large data analyses efforts and deliver high quality results for multiple projects to meet critical business deadlines.Provide written and oral presentations of methods, results, conclusions, and recommendations to peer and management groups.Collaborate with multi-disciplinary teams to develop and optimize Monsanto's global research platforms.  Qualifications:Required Skills/Experience:BS in Statistics, Biostatistics, Statistical Genetics, Math, Computer Science or related field of study.Experience manipulating, generating, reshaping, and generally molding data in a variety of forms including JSON and XML.Demonstrated development experience in Python and/or R Experience consuming REST/SOAP API's, CRUD, and client side scripting such as HTML and/or JavaScriptExperience with data queries in SQL and no-SQL databasesExperience using Git and agile development processes and/or at least 1 web authentication mechanism such as OAUTHExperience working with multi-disciplinary teams.Background in Windows and Linux operating systemsVery strong problem solving skills will be required to work well as a member of a dynamic teamStrong verbal and written communication skills.Demonstrated ability to deliver timely results and be results oriented. Desired Skills/Experience:Experience working with visualization tools such as Spotfire, Tableau, etc. and incorporating JavaScript is a plusExperience in at least one of the following programming language: Java, C++, ScalaKnowledge in standard linear and nonlinear mixed modelsMinimum of 2 years of progressive experience in Metrics/Reporting, Statistics or Plant breedingPrevious experience incorporating environmental and genetic information to inform product testing, data mining, or visualization of large databasesExperience in Bayesian hierarchical models is preferredExperience in agronomy and/or plant breeding