What are the responsibilities and job description for the Biostatistician III position at Tempus?
Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
Tempus is building a business to develop, validate, and launch new predictive tests, in oncology and new disease areas, by leveraging our clinical molecular imaging data to provide novel insights to clinicians and patients.
Purpose
The Biostatistics team at Tempus works with data scientists, clinical, and medical teams to develop statistical analysis plans (study design, statistical strategy, methods research), and execute the analyses and the study report for submissions (a regulatory body or publication) with the highest level of scientific integrity in oncology and cardiology spaces. The team works on developing statistical methods that can be implemented into the studies as well. We are seeking a highly motivated, collaborative, and capable scientific professional to join our team.
Responsibilities:
- Provide technical leadership and collaborate with stakeholders through the design and conduct of retrospective validation studies
- Lead development on statistical analysis plans -sample size and power calculations, and propose accurate and efficient statistical methodologies
- Execute study analysis, interpret the analysis results, and collaborate with stakeholders to on the study report and publication
- Provide statistical support required for any regulatory submissions
- Independent work on complex problems, and selecting and adapting novel methods as appropriate
- Collaborate in an interdisciplinary role with scientists and engineers to translate research into actionable insights for our clients
- Stay updated on the latest methodological advances in real-world data studies and clinical trials
- Comply with all regulations and Company procedures
Required Experience:
- A Ph.D. in Biostatistics, Statistics, or Epidemiology with a minimum of 3 years of relevant experience working with clinical, epidemiologic studies, or the equivalent with a Master’s
- Experience in supporting studies in oncology, cardiology, and/or genomics
- Technical expertise and knowledge of experimental design, statistical performance measures of diagnostic assay, and survival analysis (i.e., time to event analysis)
- Computational skills using R, especially relevant statistical tools and packages
Ideal candidates will possess:
- Extensive knowledge of time-to-event analysis and methodology
- Experience working in oncology and/or cardiology clinical trials and/or experience with the analysis of RWD studies (e.g. using claims, EHR or registry data sources)
- Familiarity with machine learning techniques and the advantages and disadvantages of different approaches, especially with respect to predictive and prognostic algorithms in medical research
- Experience in cancer genetics, immunology, molecular biology, or ECG prediction model
- Self-driven and works well in interdisciplinary teams
- Collaborative mindset, an eagerness to learn, and a high integrity work ethic
- Sharp attention to detail and passion for delivering high-quality and timely analytics deliverables
- Able to effectively present research results to study team and other collaborators, including results interpretation and drawing appropriate inferences based on study design/statistical methods as well as assessment of study limitations
Nice to have:
- Working experience and knowledge of FDA regulations and guidelines
- Experience with version control and software testing
- Experience supporting data science teams in model building and validation
- Client-facing or consulting experience and comfort with presenting results to stakeholders
- Proficient in SQL
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