The Stanford Pain Division in the Department of Anesthesiology, Perioperative and Pain Medicine at Stanford University is seeking a full-time Biostatistician 2 to be with some independence, consult with investigators to refine research questions, define hypotheses, design studies and devise analysis plans. Work with senior statistician(s) to implement analysis plan and publish findings. Present results orally to clinical investigators. Provide guidance to clinical investigators on design and analysis issues.
The Stanford Division of Pain Medicine merges the tripartite mission of clinical care, education, and research to advance the frontier of pain management and for those dealing with acute or chronic pain problems. The focus of the Stanford Division of Pain Medicine is the treatment of the entire patient to enable them to liver their fullest life, education of the next generation of pain physicians and healthcare leaders, and pursuing cutting edge research. If you are interested in joining a internationally recognized Pain Medicine program, please apply and take part in our research programs.
Duties include:
- Design study with an emphasis on clinical trials data. Collaborate with content experts to understand data and build appropriate statistical models to understand the data. Perform modeling building, statistical estimation, statistical inference, and modeling fitting diagnostics using off-the-shelf and custom-coded statistical programs in R or SAS
- Develop and implement protocol for quality control. Oversee data cleaning and data management of multiple datasets
- Create analytic files with detailed documentation.
- Select appropriate statistical tools for addressing a given research question.
- Implement data analysis through statistical programming. Generation of descriptive summary statistics, generation of presentation- and publication-quality charts and tables
- Present results for investigators using graphs and tables. Run preliminary analyses for PIs and summarize findings through various formats.
- Summarize findings orally and in written form. Communicate statistical model assumptions, parameter estimate interpretations, and statistical inferential conclusions to both technical and non-technical audiences.
- Participate in the preparation of papers for publication. Prepare and finalize data tables, figures, methods and results sections for manuscripts.
- 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. Offer statistical advice and consultation to PIs and collaborators
- 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.
* - Other duties may also be assigned.
DESIRED QUALIFICATIONS:
- Experience in analyzing data for NIH-funded clinical trials
- Proficient in Perl, Python, or other scripting languages for data munging.
- Skills in statistical estimation, statistical inference, and modeling fitting diagnostics.
- Proficient in R or SAS.
- Knowledge of non-parametric statistics, Bayesian methods, and small sample size methods.
- 2 year of experience doing collaborative biostatistics.
- 2 years of experience manipulating large databases programmatically.
- Experience in an academic institution, or academic hospital setting.
EDUCATION & EXPERIENCE (REQUIRED):
Master's degree in biostatistics, statistics or related field and at least 3 years of experience.
KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):
- Experience in analyzing data for NIH-funded clinical trials
- 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 MySQL); graphical techniques (e.g., expertise in Illustrator).
PHYSICAL REQUIREMENTS*:
- Frequently perform desk-based computer tasks, seated work and use light/fine grasping.
- Occasionally stand/walk, reach/work above shoulders, grasp lightly/fine manipulation, grasp forcefully, use a telephone, sort/file paperwork or parts, lift/carry/push/pull objects that weigh up to 10 pounds.
- Frequently sitting.
- Rarely twist/bend/stoop/squat, kneel/crawl.
* - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
WORKING CONDITIONS:
- May work extended or non-standard hours based on project or business cycle needs.
WORK STANDARDS (from JDL)
- Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
- Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
- Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, http://adminguide.stanford.edu
The expected pay range for this position is $107,000 - $125,000 per annum. The actual pay will be pro-rated based on the 50% FTE.
Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.
