Sr. Biostatistician

Responsibilities

• Partner with stakeholders to translate scientific research questions into well-defined statistical problems, prioritize project goals, and deliver actionable results through clear written and verbal communication.
• Design, execute, and troubleshoot statistical analyses across a portfolio of projects using methods such as dose-response modeling, mixed models, GLMs, multivariate analyses, and nonparametric approaches.
• Evaluate and improve experiment designs using data and simulation, including power analyses and characterization of sources of variation.
• Collaborate with engineering teams to integrate statistical scripts into production workflows, including troubleshooting pipeline error.
• Quantify assay correlations and cross-platform/cross-stage translation to support critical decisions for trait advancement.
• What Skills You Need:
• M.S. in Statistics, Biostatistics, or a closely related quantitative field with 5+ years of industry experience, or Ph.D. with 3+ years of industry experience.
• Strong applied statistics background including mixed models, GLMs, dose-response modeling, multivariate analyses, non-standard distributions, and design of experiments.
• Experience working with biological data types including bounded (proportion/percentage) and ordinal data, qualitative and quantitative assay outputs.
• Working knowledge of specialized methods relevant to biological data, including ordinal logistic regression, censored data models, and beta regression.
• A collaborative mindset, including the ability to ask clarifying questions, navigate ambiguity, and co-develop statistical solutions with non-statistical partners across a project portfolio.
• Proficiency in a statistical programming language (R strongly preferred); candidates working in other languages must demonstrate ability to validate code translations rigorously, including through AI-assisted tooling.

Requirements

• Experience in agricultural biology, plant science, or a related life science domain (e.g., trait discovery, greenhouse or field research, molecular diagnostics, in-vitro or in-planta assay systems).
• Familiarity with software deployment practices, version control (e.g., Git), and collaborating with data and ML engineers to productionize analytical workflows.
• Exposure to simulation-based methods for experiment design optimization and power analysis in complex biological systems.
• #LI-BB1
• Benefits - How We'll Support You:
• Numerous development opportunities offered to build your skills
• Be part of a company with a higher purpose and contribute to making the world a better place
• Health benefits for you and your family on your first day of employment
• Four weeks of paid time off and two weeks of well-being pay per year, plus paid holidays
• Excellent parental leave which includes a minimum of 16 weeks for mother and father
• Future planning with our competitive retirement savings plan and tuition reimbursement program
• Learn more about our total rewards package here - Corteva Benefits
• Check out life at Corteva! www.linkedin.com/company/corteva/life
• Are you a good match? Apply today! We seek applicants from all backgrounds to ensure we get the best, most creative talent on our team.

Benefits

Additional Information

Corteva Agriscience is a global leader of seed, crop protection, and digital solutions in agriculture. We have an opening in our Seeds R&D team for an experienced Sr. Biostatistician to accelerate the discovery and delivery of next-generation biotechnology traits to the farmers that depend on them. This position supports a portfolio of research projects at the intersection of biology and quantitative science, contributing to critical decisions in trait discovery and development . The role applies strong statistical fundamentals to a diverse range of biological data types, including in-vitro, in-planta, and molecular assays, spanning qualitative and quantitative outputs, bounded data, and non-standard distributions. The successful candidate will operate as a dedicated partner to the Biotechnology organization , working closely with research scientists and engineers to shape critical research decisions while also benefiting from a broader community of peers in statistics and data science. The ideal candidate brings genuine curiosity about the underlying biology and an enthusiasm for understanding how assays contribute to the R&D pipeline.

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