YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role, Senior Data Scientist Analytics and Modeling, are to: 

• Provide technical contributions in a fast-paced team environment to accelerate our efforts on building an analytics-driven product pipeline;
• Improve Plant Breeding strategies by designing experiments, developing algorithms and building statistical models that optimize the use of phenomics and genomic data;
• Work with teams of software and data engineers to integrate novel genomics technologies into automated pipelines and production workflows;
• Assess needs and recommends experiments and projects, suggest new algorithmic development, drive tactical decisions about approaches and needed data;
• Use advanced mathematical models, machine learning algorithms, operations research techniques and strong business acumen to deliver insight, recommendations and solutions;
• Contribute to the development of code, bioinformatic analyses pipelines, computational tools and databases for mining and visualizing large genomic data sets;
• Demonstrate full autonomy in developing relationships for effective cross-functional collaboration throughout multiple organizations and partner on work stream initiatives for Data Science Community;
• 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;
• Develop Code (20-25%);
• Stats/Modeling Research (30-35%);
• Domain Knowledge and Consulting Industry Experts (30-35%);
• Provide Technical Guidance to Associate DS and DS, mentors, develops and delivers presentations and strategies: (10-15%).

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 eight years of experience or Master’s degree with at least six years of experience or Ph.D. with at least three years of experience;
• Educational preparation or applied experience in Machine Learning, Electrical/Industrial Engineering, Operation Research, Statistical or Quantitative Genetics, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology, Applied Mathematics, Computer Science or other related quantitative discipline;
• Strong proficiency in computational skills;
• Skilled at the intermediate level building data models using R, Python or other statistical and/or mathematical programming packages;
• Ability to demonstrate advanced professional competencies in linear modeling, scientific modeling and development and application of increased domain knowledge;
• Proficiency in standard suite and/or modeling theories;
• Familiarity with code repositories like GitHub;
• Experience working in cloud computing environments;
• Intermediate proficiency in machine learning algorithms and concepts;
• Extensive experience in successful delivery of valuable analysis through application of domain knowledge;
• Evidence of strong business acumen;
• Ability to manage a larger more diverse and complex project/program;
• Strong communication competencies to include presentations and delivery of complex quantitative analyses in a clear, concise and actionable manner to broad audiences and key stakeholders across multiple functions.