Data Scientist I

Position Overview

The Data Scientist I role involves providing statistical consultation to faculty, staff, and graduate students engaged in applied research within agriculture, natural resources, and life sciences fields. Responsibilities include assisting researchers in framing research questions, selecting suitable statistical methodologies, examining experimental setups, organizing data, and interpreting analytical results.

Primary Duties

• Conduct statistical consulting on research projects, covering topics such as experimental design, ANOVA, regression, linear and generalized linear models, mixed models, repeated measures, and multivariate analysis relevant to IFAS research.
• Execute reproducible statistical analyses primarily using R and/or Python, with supplementary use of SAS, JMP, Stata, or SPSS as necessary. Tasks encompass data cleaning, exploratory analysis, model development and diagnostics, summarizing findings, visualizing results, and communicating analytic methods clearly to non-statistical researchers.
• Support preparation of high-quality publication-ready materials including tables, figures, statistical summaries, descriptive methods, reports, abstracts, manuscripts, and grant documents that accurately present statistical results.
• Develop and maintain statistical workflows, reproducible analysis scripts, and training content aimed at common consulting needs; this may include exploring and evaluating R packages, Python tools, Shiny applications, Google Colab notebooks, and Jupyter notebooks to enhance research and consultation effectiveness.
• Assist in delivering training sessions, workshops, short courses, and practical tutorials focused on applied statistics, experimental design, data visualization, and reproducible workflows targeted at faculty, staff, and students.
• Contribute to online resource development for the Statistical and Data Analytics Consulting Unit, including FAQs, example workflows, guidance documents, and training materials addressing research design and data analysis challenges.

Qualifications

• Required: Bachelor's degree in data science, statistics, bioinformatics, analytics, or related fields with two years of relevant experience; or a Master's degree in these disciplines.
• Preferred: Master's degree in applied or agricultural statistics, biostatistics, quantitative ecology, or closely related quantitative fields with emphasis on agriculture, natural resources, or life sciences.
• Minimum two years applying statistical methods to real-world research data in academic, consulting, or graduate-level environments with expertise in experimental design, regression, ANOVA, linear and generalized linear models, mixed models, and repeated-measures analysis.
• Proficient use of R and/or Python for statistical analyses and reproducible data workflows, with the ability to clearly communicate complex statistical concepts to researchers without statistical backgrounds.
• Experience with agricultural, biological, environmental, plant science, animal science, ecological, or related datasets preferred.
• Excellent communication and interpersonal skills suited to collaborative academic or research teams.
• Track record in statistical consulting, including helping define research aims, method selection, explaining assumptions, and result interpretation.
• Advanced knowledge of specialized statistical techniques such as linear mixed models, Bayesian analysis, longitudinal data analysis, spatial analysis, multivariate methods, and relevant experimental designs.
• Competence with statistical software environments including R, SAS, JMP, Stata, SPSS, with an emphasis on reproducible, well-documented analysis scripts and preparing publication-quality materials.
• Experience in developing and presenting educational materials such as workshops, tutorials, handouts, and training sessions on applied statistics and reproducible research.
• Familiarity with applied machine learning, AI, deep learning, or data science methods applied to biological or agricultural research regarded as advantageous but complementary.

Additional Information

This position offers an estimated annual salary of $61,000. Candidates must submit a cover letter and resume for consideration. The application deadline is at 11:55 p.m. Eastern Time of the posting end date. No health assessment is required for this role.