Job Description

YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role, Digital Development Senior Scientist, are to: 

Complete statistical analysis and analytical modeling as needed by the North America (NA) Breeding Pipeline to drive NA breeding strategy;
Assess needs and recommends experiments and projects, suggests 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;
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 (KPI);
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;
Coach other members of the team.

Domestic relocation as well as visa sponsorship is available.

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 M.Sc. degree with at least six years of experience OR Ph.D. with at least three years in Life Sciences, Statistics or Data Science;
Strong knowledge of computational skills and experience doing statistical analysis, modeling, and data processing 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;
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.