Epidemiologic & Biostatistical Data Scientist
Durham, NC, US, 27710
Duke University
School of Medicine
Established in 1930, Duke University School of Medicine is the youngest of the nation's top medical schools. Ranked sixth among medical schools in the nation, the School takes pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where interdisciplinary collaboration is embraced and great ideas accelerate translation of fundamental scientific discoveries to improve human health locally and around the globe. Composed of more than 2,600 faculty physicians and researchers, nearly 2,000 students, and more than 6,200 staff, the Duke University School of Medicine along with the Duke University School of Nursing, and Duke University Health System comprise Duke Health, a world-class academic medical center. The Health System encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations.
Epidemiologic & Biostatistical Data Scientist
The Department of Family Medicine and Community Health in the Duke University School of Medicine is dedicated to improving the health of people in their communities. Duke Family Medicine and Community Health's diverse group of full-time researchers, as well as clinical and education faculty, are actively engaged in a wide variety of disciplines with research encompassing a broad collection of clinical, community and population health research programs, drawing on an eclectic set of analytical methods and tools.
Occupational Summary
This position will play a critical role in advancing quantitative research for the Operation Deep Dive Study, a large-scale study investigating deaths of despair, suicide, non-suicidal self-harm, and other causes of premature mortality among former U.S. military service members do we. The study examines how military service characteristics and demographic factors predict premature mortality and compares these rates to national averages to inform policy and clinical interventions.
The successful candidate will work in a team science framework, managing large, complex data environments, developing analysis plans and collaborating with team members on potential solutions to data needs, applying advanced statistical modeling to observational, epidemiologic, and real-world data, and communicating results to team and external stakeholders in an effective manner. This role requires technical expertise, strategic problem-solving skills, and effective communication to ensure research findings are accurate, reproducible, and actionable. The candidate must be able to work in a fast-paced environment, delivering high-quality results on time while maintaining flexibility in adapting approaches based on study needs.
Work Performed
Data Management, Cleaning, and Reporting (45% initially, decreasing to 20% as the project progresses)
- Independently conduct exploratory analyses and visualizations to inform team-based decision-making.
- Identify and evaluate missing data issues, developing and presenting solutions to investigators to guide decision-making on analysis approaches.
- Create detailed reports summarizing data management and cleaning processes to support Principal Investigator (PI) decisions regarding data processing strategies.
- Develop and implement standardized data cleaning and integration workflows for large, multi-source datasets, including death certificate data and Department of Defense personnel files.
- Use probabilistic matching, deterministic linkage, and entity resolution strategies to merge disparate datasets while ensuring accuracy.
- Apply imputation techniques (e.g., multiple imputation, expectation-maximization, inverse probability weighting) to address missing data.
- Detect and resolve data inconsistencies and outliers using statistical anomaly detection methods and automated validation checks.
- Ensure reproducibility by maintaining clear, well-documented data transformation workflows, metadata tracking, and transparent audit trails.
Statistical Analysis, Modeling, and Analysis Planning (20% initially, increasing to 45% as the project progresses)
- Develop, draft, and implement analysis plans that outline statistical methodologies, algorithms, and decision criteria for complex observational datasets.
- Apply statistical approaches to address confounding, bias, and data structure complexities, for example, using propensity score methods, inverse probability weighting, causal inference techniques, multilevel and hierarchical models, latent class analysis, and predictive modeling techniques.
- Conduct standard epidemiologic risk factor modeling as well as direct and indirect standardization methods to compare military versus civilian mortality rates.
- Evaluate and present methodological options to investigators, allowing for informed decisions on analysis approaches.
- Perform sensitivity analyses and robustness checks to validate findings across multiple statistical methodologies.
- Clearly document and communicate analytical choices, ensuring that results are interpretable, actionable, and reproducible.
Team Collaboration and Communication (20%)
- Actively engage in regular team meetings, providing timely progress updates to project managers, investigators, and the statistical team.
- Collaborate with multidisciplinary teams, including researchers, clinicians, and data managers, to ensure analytical strategies align with broader study objectives.
- Prepare high-quality documentation, analysis reports, and presentation materials, ensuring that findings are communicated clearly to diverse stakeholders.
Leadership and Mentorship (5%)
- Take initiative as a strong leader and team member, actively providing guidance to students and supporting team-based analytical approaches.
- Identify potential statistical and operational risks, proposing solutions to optimize efficiency and analytical rigor.
- Contribute to innovative problem-solving, offering new methodological approaches and improvements to data standardization and analysis workflows.
Support for Dissemination (5%)
- Assist with drafting abstracts, manuscripts, and methods sections, integrating analytical results with team input to ensure clarity, rigor, and impact.
- Develop and refine presentation materials—including slides for conferences, seminars, and poster sessions—to highlight key insights and innovations.
- Contribute to strategies that enhance the visibility of the study’s findings, ensuring research findings inform policy, clinical practice, and future investigations.
Regulatory, Data Security, and Reproducibility (5%)
- Stay up to date on regulatory standards governing research activities and data security protocols.
- Follow best practices in reproducible research, including version control, standardized reporting formats, and detailed procedural documentation.
- Adhere to standard operating procedures, ethical guidelines, and institutional policies for working with sensitive data.
Minimum Qualifications
Education
- Master’s degree or equivalent in economics, public policy, public health, statistics, biostatistics, bioinformatics, data science, or a related field with 2 years of relevant experience; or an equivalent combination of education and work experience; or a doctoral degree in a related field.
Experience
- Proven proficiency in SAS, STATA, or R, with prior contributions to research projects involving complex data analysis.
- Experience processing and analyzing large, multi-source datasets, with the ability to execute statistical analyses, develop analytical reports, and maintain high-quality documentation on time.
- A track record of working in fast-paced research environments, ensuring that data processing, analysis, and reporting are accurate, efficient, and adaptable to evolving study needs.
Preferred Qualifications
- Experience developing and documenting innovative analytic strategies for observational studies with a research team
- Strong ability to work collaboratively while independently executing statistical and data management tasks.
- Ability to think critically about data challenges and proactively develop solutions to improve study execution.
Minimum Qualifications
Duke is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity , genetic information, national origin, race, religion, sex, sexual orientation, or veteran status.
Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas—an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have a responsibility to uphold these values.
Anticipated Pay Range:
Duke University provides an annual base salary range for this position as USD $98,009.00 to USD $158,364.00. Duke University considers factors such as (but not limited to) scope and responsibilities of the position; candidate's work experience, education/training, and key skills; internal peer equity; as well as market and organizational considerations when extending an offer.
Your total compensation goes beyond the dollars on your paycheck. Duke provides comprehensive and competitive medical and dental care programs, generous retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at: https://hr.duke.edu/benefits/
Essential Physical Job Functions: Certain jobs at Duke University and Duke University Health System may include essential job functions that require specific physical and/or mental abilities. Additional information and provision for requests for reasonable accommodation will be provided by each hiring department.
Education
Position requires a minimum of a Doctoral degree in (bio) statistics or related field and no relevant experience, or a Master's degree in (bio)statistics or related field and 2 years relevant experience, or a Bachelor's degree in (bio) statistics or related field and 4 years relevant experience.
Experience
OR AN EQUIVALENT COMBINATION OF RELEVANT EDUCATION AND/OR EXPERIENCE Contribution to analysis of clinical trials and/or clinical research projects, and/or participation in preparation of academic manuscripts or other written summaries of analysis results, thorough experience with SAS, and solid command of the English language is required. Desirable experience includes prior role as a lead statistician on clinical trials and/or clinical research projects that have delivered the agreed-upon end products on time, and prior guidance of lower level or less experienced staff.
Duke is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status.
Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas—an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have a responsibility to uphold these values.
Essential Physical Job Functions: Certain jobs at Duke University and Duke University Health System may include essentialjob functions that require specific physical and/or mental abilities. Additional information and provision for requests for reasonable accommodation will be provided by each hiring department.
Tags: Bioinformatics Biostatistics Causal inference Data analysis Data management Economics Predictive modeling R Research SAS Security Stata Statistical modeling Statistics
Perks/benefits: Competitive pay Conferences Equity / stock options Health care Wellness
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