Biostatistician

As a Statistical Analyst for biomarker discovery, your role will involve: Aid in the planning and writing of biomarker statistical analysis plans in the lead-up to clinical trials. Run and develop statistical modelssuch as random effects, mixed effects, and MMRM modelson biomarker data once clinical trials conclude. Support discovery research by reviewing literature and conducting power analyses to determine the efficacy of exploratory biomarkers. Work flexibly within a US time zone to collaborate with local stakeholders and act as a bridge for the current team members based in India. To excel in this role, you should meet the following qualifications: A highly formalized and solid background in statistical analysis. Strong capability to understand experimental design in scientific literature, formulate null and alternate hypotheses, and identify the appropriate statistical models or tests. Deep comprehension of how statistical models function and the core assumptions required to run and check them in the biomarker discovery space. Proficiency in programming with Python or R (Note: SAS coding is not required for this role). Must be located in a US time zone (such as the East Coast or Midwest) to enable real-time collaboration with US-based team members. Additionally, it is preferred that you have the following skills: Familiarity with CDISC standards, specifically experience working with ADaM or SDTM datasets. Experience or subject-matter knowledge in neuroscience and eye care (Scott's team), the broader team also supports oncology and immunology. Prior experience with biomarker discovery projects. As a Statistical Analyst for biomarker discovery, your role will involve: Aid in the planning and writing of biomarker statistical analysis plans in the lead-up to clinical trials. Run and develop statistical modelssuch as random effects, mixed effects, and MMRM modelson biomarker data once clinical trials conclude. Support discovery research by reviewing literature and conducting power analyses to determine the efficacy of exploratory biomarkers. Work flexibly within a US time zone to collaborate with local stakeholders and act as a bridge for the current team members based in India. To excel in this role, you should meet the following qualifications: A highly formalized and solid background in statistical analysis. Strong capability to understand experimental design in scientific literature, formulate null and alternate hypotheses, and identify the appropriate statistical models or tests. Deep comprehension of how statistical models function and the core assumptions required to run and check them in the biomarker discovery space. Proficiency in programming with Python or R (Note: SAS coding is not required for this role). Must be located in a US time zone (such as the East Coast or Midwest) to enable real-time collaboration with US-based team members. Additionally, it is preferred that you have the following skills: Familiarity with CDISC standards, specifically experience working with ADaM or SDTM datasets. Experience or subject-matter knowledge in neuroscience and eye care (Scott's team), the broader team also supports oncology and immunology. Prior experience with biomarker discovery projects.