Senior Biostatistician

Baylor College of Medicine; Houston (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Baylor College of Medicine is seeking a Senior Biostatistician to lead statistical methods and analyses within the Cardio-Oncology Epidemiology Program. You will design studies, perform advanced analyses of clinical datasets, and contribute to publications and presentations.

The role requires translating complex statistics for multidisciplinary teams and managing multiple priorities in a dynamic research environment.

Qualifications

• Master's Degree in Statistics, Biostatistics or a related field.
• Three years of relevant experience.
• PhD in Biostatistics, Statistics, Epidemiology, or related field preferred.

Responsibilities

• Performs statistical analysis and interpretation of data for projects and grants.
• Applies longitudinal, survival, recurrent event, multilevel data methods.
• Develops reproducible analytic workflows using R, SAS and SQL.
• Manages analytic timelines across multiple projects within the Center for Epidemiology and Population Science.
• Produces publication-quality tables, figures and summaries for journals and conferences.
• Presents results to investigators and team members.
• Develops analysis plans for clinical trials and observational studies using causal inference methods.

Skills

EHR data experience

Large observational datasets

Cardiovascular outcomes research

Oncology survivorship research

Health services research

Statistical analysis experience

Education

Master's Degree in Statistics or Biostatistics

PhD in Biostatistics, Statistics, Epidemiology, or related field

Tools

R

SAS

SQL

Job description

Work Schedule: Monday – Friday, 8 a.m. – 5 p.m.

Summary

The Section of Oncology Epidemiology within the Department of Pediatrics and Texas Children's Cancer Center is seeking a highly motivated Senior Biostatistician to serve as a key contributor to the newly-formed Cardio-Oncology Epidemiology Program. The position will independently develop and implement statistical methodologies, contribute to study design, perform advanced analyses of complex clinical datasets, and support dissemination of findings through peer-reviewed publications and scientific presentations. The ideal candidate will have excellent analytic and problem-solving skills, demonstrate scientific rigor and a capacity to translate complex statistical concepts for multidisciplinary audiences, and the ability to manage multiple priorities in a dynamic and growing research environment.

Job Duties

• Data Analysis and Reporting
  • Performs statistical analysis and interpretation of data for projects and research grants.
  • Performs advanced statistical analyses using longitudinal, survival, recurrent event, multilevel data methodologies.
  • Develops reproducible analytic workflows utilizing R, SAS, SQL, and other statistical software platforms.
  • Manages analytic timelines and deliverables across multiple projects within the Center for Epidemiology and Population Science.
  • Maintains comprehensive analytic documentation, including data dictionaries, codebooks, annotated programming scripts, and version-controlled research files to support transparency and reproducibility.
  • Produces publication-quality tables, figures, and technical summaries for publication in conference proceedings, peer-reviewed manuscripts, preprint servers, and other scientific forums.
  • Effectively interacts and presents results to investigators and team members.
• Statistical Experimental Design
  • Develops statistical programs for data manipulation and implementation of standard and advanced statistical methodology.
  • Develops statistical analysis plans for clinical trial and observational research studies employing contemporary causal inference methodologies (e.g., mediation analyses, trial emulation).
  • Develops and implements analytic approaches to evaluate data quality, missing data mechanisms, confounding, selection bias, and measurement error, and estimate the impact on observed results.
  • Performs simulation studies and methodological evaluations for observational and clinical research.
  • Contributes to development and refinement of novel analytic approaches for cardiovascular outcomes and population health research.
  • Provides statistical review and contribution to manuscripts, abstracts, protocols, and grant applications prior to submission.
• Assists in training lower-level data management team members.
• Participates in scientific working groups and investigator meetings.
• Assists investigators in evaluating feasibility of proposed projects.
• Assists in developing Program/Section standard operating procedures (SOPs) as needed.
• Establishes analytic standards, quality control procedures, and reproducibility practices.
• Complies with all applicable institutional, state, and federal data security requirements.
• Performs other job duties as assigned.

Minimum Qualifications

• Master's Degree in Statistics, Biostatistics or a related field.
• Three years of relevant experience.

Preferred Qualifications

• PhD in Biostatistics, Statistics, Epidemiology, or related field.
• Experience working with EHR, claims, registry, or large observational datasets.
• Experience with cardiovascular outcomes research, oncology, survivorship, pharmacoepidemiology, or health services research.

Work Authorization Requirement:

This position is not eligible for visa sponsorship.Candidates must be legally authorized to work in the United States at the time of application and throughout the duration of employment.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.

Baylor College of Medicine fosters diversity among its students, trainees, faculty, and staff as a prerequisite to accomplishing our institutional mission and setting standards for excellence in training healthcare providers and biomedical scientists, promoting scientific innovation, and providing patient-centered care. Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.