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Employment type:
Full time
Experience required:
Intermediate
Salary
Salary not provided
About the company:
About Inari...
Inari is the SEEDesign™ company. We embrace the diversity and complexity of nature in every aspect of our business to drive innovation – to push the boundaries of what is possible. Through our unrivaled technology platform, Inari uses predictive design and advanced multiplex gene editing to develop step-change products. We are taking a nature positive approach to unlock the full potential of seed that will transform the food system. The results will lead to more productive acres delivering value creation for farmers and a more sustainable future for our planet.
Our success is dependent on great minds, collaborating to generate bright ideas and deliver exceptional outcomes.
We have over 270 employees, with research sites in Cambridge, MA (USA) and Ghent (Belgium), as well as a product development site in West Lafayette, IN (USA). We’ve deliberately built a team that brings diversity of thought to all aspects of our business, to generate new ideas, approaches, and ways of operating. And we've intentionally combined experience with potential, bringing agriculture industry experts with the desire to innovate together with bright minds from academia, human therapeutics, software, and consulting. If you want to be part of a diverse and inclusive team developing unique solutions to feed the world while protecting our planet’s natural resources, we’d love to hear from you!
ABOUT THE ROLE....
We are looking for a dynamic and highly motivated statistician who is committed and passionate about
the implementation of cutting-edge technology in plant breeding to accelerate genetic gain. You will bring
your expertise in statistics to boost Inari’s ability to fundamentally transform plant breeding. As an applied
statistician, you will help drive and execute Inari’s scientific strategy through experimental design
optimization and implementation of advanced statistical modeling on the data from research pipelines.
AS APPLIED STATISTICIAN, YOU WILL…
· Identify and help solve problems related to experiment design and statistical analyses for
studies in lab, green-house, and field.
· Identify limitations for improvement with existing methodologies using advanced statistical
methodologies.
· Perform inferential analyses, including documentation, to support decision-making and patent
submissions, publications, and scientific presentations.
· Assist in modernizing our field trialing system by implementation of imagery technology and
spatial analyses to gain insights and enhance decision making.
· Provide oversight of CROs statistical and programming support for outsourced statistical
activities as well as QC key results generated by CROs.
YOU BRING…
· MS (with 1+ years of experience) or PhD in statistics or biostatistics, or PhD in crop science
with statistics degree
· Demonstrated proficiency in wide range of statistical techniques including experimental design,
general and generalized linear mixed models, non-linear mixed models, multivariate statistics,
non-parametric analysis, and Bayesian statistics.
· Demonstrated proficiency of teamwork across disciplines of statistics, plant science, and data
engineering.
· Proficiency in the R, SAS, and other programming language.
· Strong communication skills to include presentations and delivery of complex quantitative
analyses in a clear, concise, and actionable manner to extended team and small groups of key
stakeholders.
BONUS QUALIFICATIONS…
· Formal training and/or experience in plant science research.
· Solid experience in AWS or Google Cloud.
· Demonstrated proficiency in machine learning algorithms and concepts for imagery data.
FOR U.S. CANDIDATES: Please note that we use the resume you submit with your application during our background check process. To ensure an efficient and accurate background verification, we kindly ask that you carefully review and accurately represent your work history, education and other relevant information on your resume. Any discrepancies or inaccuracies found during the background check may impact your candidacy for the position.
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