Biostatistician 2 (1-Year Fixed-Term, Hybrid Opportunity)

Apply a variety of intermediate and advanced statistical techniques and technical skills to collect, analyze, and interpret data resulting from research studies.

The mission of the QSU is to facilitate cutting-edge scientific studies initiated by Stanford investigators by providing expertise in biostatistics and informatics, to mentor and educate clinical investigators in research methods, and to mentor data scientists so that they can reach their full potential.  The QSU achieves its mission through an interdisciplinary collaborative approach where QSU members become fully integrated into individual research teams.

This is a 1-year fixed-term, hybrid opportunity.

Responsibilities

• Core Duties: Design study.
• Develop and implement protocol for quality control.
• Create analytic files with detailed documentation.
• Select appropriate statistical tools for addressing a given research question.
• Implement data analysis through statistical programming.
• Present results for investigators using graphs and tables.
• Summarize findings orally and in written form.
• Participate in the preparation of papers for publication.
• Consult with investigators on appropriate statistical approaches to data analyses; assist in study design and proposal development.
• Mentor collaborators in areas of experimental design, quality control, and statistical analysis
• Develop oral and written dissemination of findings for conference presentations and peer-reviewed journal articles.
• Oversee lower-level staff on issues related to quality control and creation of analysis files.
• Minimum Education and
• Experience
• Master’s degree in biostatistics, statistics or related field and three years of experience.
• Knowledge, Skills and Abilities: Proficient in at least two of R, SAS, SPSS, or STATA.
• Skills in descriptive analysis, modeling of data, and graphic interfaces.
• Outstanding ability to communicate technical information to both technical and non-technical audiences.
• Demonstrated excellence in at least one area of expertise, which may include coordinating studies; statistical methodology such as missing data, survival analysis, statistical genetics, or informatics; statistical computing; database design (e.g., expertise in RedCAP or