Job Description:

The Statistical Team lead will provide statistical consulting to scientists and breeders in designing experiments for product and trait evaluation, QTL detection, validation, fine mapping, and data QC. This position will assist scientists in the analysis and interpretation of data, the testing of innovative ideas, and will conduct training in statistical methods and software applications. This position will be informed of statistical advances (especially with regard to field design and marker-trait association theory), as well as software capabilities and share this knowledge with colleagues in the company’s Global Native Trait Projects and Genetic Information teams. This role will supervise the statistical team, conduct analysis, prioritize competing projects, and provide advice on questions of statistical approach, and assist in adjusting staffing, identify educational needs, and work with the IT organization to identify and develop statistical tools for molecular breeding applications. Accountabilities 1. Provide scientific leadership in Corn and Soybean trait and molecular breeding research. 2. Help in the development or improvement of protocols and methodologies for marker-trait breeding related projects, in compliance with corporate IT guidelines. 3. Provide support for standard statistical software and make recommendations for improvements. 4. Seek commonality in approaches for statisticians and biometricians across regions. 5. Assure that innovative methods are documented to meet intellectual property guidelines. 6. Work with across functional teams (Marker Trait Association Group, Genetic Information Managers, Trait Genetics) and Native Trait Project teams to facilitate and optimize molecular breeding approaches.

• Self-motivated, detail oriented, and excellent analytic and leadership skills. • Ability to interface with multiple functions and departments. • Strong interpersonal, organizational, and communication skills. Critical knowledge • Ph.D in Statistics or related discipline, or MS with a minimum of 4 years of professional experience. • Graduate level training in agronomy, plant or animal breeding, genetics, bioinformatics, or related agricultural or life sciences field is highly desired. • Proficient knowledge of Experimental Design (including multivariate methods such as PCA and cluster analysis preferred) with regard to field-based trial design. Critical experience • Experience in educating or training of individuals or groups and/or web-based coursework training. • Experience coordinating large, complex projects or formal Project Management training. • Skilled with commercial applied statistical software (e.g. SAS, JMP, S-PLUS, R, ASREML, GGE Biplot) or customized programs (Fortran, C++) for experimental design and data analysis • Experience working with large datasets. • Prefer experience with mixed models (BLUP). • Ability to organize and manage workload of multiple tasks in an effective manner. Critical technical, professional and personal capabilities • Strong interest in applied statistical analysis with the ability to innovate, in order to solve potentially complex statistical problems. • Capability and desire to empower scientific colleagues to have a greater comprehension of information generated by experiments, and help them identify when additional expertise is required. • Ability and motivation to help refine the company’s course for scientific inquiry to further uncover the potential of plants to improve the lives and profitability of our customers. Critical leadership capabilities • Team-Oriented • Customer-Focused • Results-Oriented • Communicative • Analytical Thinking

• Work with a global multidisciplinary team of geneticists, plant breeders, statisticians, data analysts, and other project scientists.

• A minimum of 2 years in current position is required (requirement for internal applicants only). • All applicants must be eligible to work in the US. • Frequent travel by car or plane. • Periods of intense computer or field work at critical times for projects. • Indoor – extensive work at a computer for long periods of time.