Biostatistician III - CSTS

Join the HJF Team!

HJF is seeking a Biostatistician III to provide biostatistical support for a large-scale research study. This involves the design, implementation, and validation of statistical models, risk prediction tools, and causal analyses, as well as performing advanced statistical analysis on data collected from research studies.

Project Summary: The Suicide Avoidance Focused Enhanced Group Using Algorithm Risk Detection (SAFEGUARD) research initiative will use machine learning and predictive analytics to identify soldiers at greatest risk for suicide, and deliver targeted interventions, trainings, and psychoeducation programs aimed at mitigating risk for suicide and other harmful behaviors. SAFEGUARD consists of three projects - Life Skills, Life Force, and Pathfinding - that will evaluate the effectiveness of three different targeted interventions.

This position will be in support of the Department of Psychiatry / Center for the Study of Traumatic Stress. based out of Bethesda, MD.

The Center for the Study of Traumatic Stress (CSTS) is one of the nation's oldest and most highly regarded, academic-based organizations dedicated to advancing trauma-informed knowledge, leadership and methodologies. The Center's work addresses a wide scope of trauma exposure from the consequences of combat, operations other than war, terrorism, natural and human-made disasters, and public health threats as well as risk and protective factors associated with suicidal behaviors. CSTS is a part of our nation's federal medical school, Uniformed Services University (USU), and its Department of Psychiatry. These affiliations represent the Center's history, mission and future directions as a major contributor to our country's understanding of the impact of trauma and the advancement of trauma-informed care. Learn more about the CSTS.

The Department has active research programs in the Basic and Clinical Sciences and Neurosciences. In addition to intramural research projects, the Department maintains active research funded by the National Institute of Mental Health, National Institute of Drug Abuse, National Science Foundation, the Department of the Army and the Department of the Air Force. The department has ongoing collaborations with the Walter Reed Army Institute of Research, is sponsor of the Center for the Study of Traumatic Stress and provides psychiatry residency training through its affiliations with Walter Reed National Military Medical Center, National Naval Medical Center and Malcolm Grow Air Force Medical Center and the National Capital Area Graduate Medical Education Consortium.

The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF) is a nonprofit organization dedicated to advancing military medicine. We serve military, medical, academic and government clients by administering, managing and supporting preeminent scientific programs that benefit members of the armed forces and civilians alike. Since its founding in 1983, HJF has served as a vital link between the military medical community and its federal and private partners. HJF's support and administrative capabilities allow military medical researchers and clinicians to maintain their scientific focus and accomplish their research goals.

• Partner with Principal Investigators and other scientists to define analytic objectives and select appropriate statistical methods to achieve project goals.
• Take a leadership role in development, implementation, and validation of statistical models, prediction tools, and causal analyses on technically challenging projects involving ML, natural language processing (NLP), and large-scale experimentation; ensure methods are rigorous, reproducible, and well documented.
• Perform and oversee advanced statistical analyses (e.g., generalized linear and mixed models, longitudinal modeling, survival analysis, causal inference, RCT and quasi-experimental designs).
• Provide statistical support and consultation on power and sample size calculations, randomization schemes, statistical analysis plans, and protocol development.
• Apply state-of-the-art machine learning methods to build, test, and operationalize algorithmic tools that support robust empirical research.
• Employ causal inference methods (e.g., propensity score methods, marginal structural models, instrumental variables) to address confounding and strengthen causal interpretation of findings.
• Develop realistic analytic timelines, identify resource needs, and manage project plans; monitor progress and proactively address risks to ensure milestones are met.
• Communicate analytic strategies, assumptions, interim results, and implications to project teams, scientific leadership, collaborators, and funders.
• Prepare clear and accurate statistical summaries, technical memoranda, and reports for internal stakeholders, funders, regulatory bodies, and other external partners.
• Contribute to peer-reviewed manuscripts, conference abstracts, presentations, and reports for lay audiences.
• May perform other duties and responsibilities as assigned or directed by the supervisor. This may include attendance of and participation in required training for role.

Education and Experience

• Bachelor's Degree in Biostatistics, Statistics, Epidemiology, or a closely related field.
• Minimum of 9-10 years experience required.

Required Knowledge, Skills and Abilities

• Deep knowledge of biostatistics, epidemiologic methods, and study design (experimental and observational) required.
• Demonstrated expertise with complex data structures, including longitudinal, multilevel, and repeated-measures data required.
• Advanced proficiency in statistical programming (e.g., R and/or SAS) for data management, advanced modeling, simulation, and reproducible workflows (e.g., version control, literate programming) required.
• Experience with additional software (e.g., STATA, MPlus, HLM, Python) is highly desirable.
• Familiarity with deploying analytic software and workflows in cloud environments (e.g., AWS, Azure) and working with large, secure datasets.
• Proven ability to communicate complex statistical concepts and results clearly to both technical and non-technical audiences, verbally and in writing.
• Strong leadership, team-building, and project management skills.
• Ability to obtain and maintain a T1/Public Trust background check.

Work Environment

• This position will be fully remote.

Compensation

• The annual salary range for this position is $93,100 -$135,000. Actual salary will be determined based on experience, education, etc.

Benefits

• HJF offers a comprehensive suite of benefits focused on your health and well-being, from medical, dental, and vision coverage to health savings and retirement plans, and more.

Employment with HJF is contingent upon successful completion of a background check, which may include, but is not limited to, contacting your professional references, verification of previous employment, education and credentials, a criminal background check, and a department of motor vehicle (DMV) check if applicable. Any qualifications to be considered as equivalents, in lieu of stated minimums, require the prior approval of the Chief Human Resources Officer.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information. 41 CFR 60-1.35(c)

Any qualifications to be considered as equivalents, in lieu of stated minimums, require the prior approval of the Chief Human Resources Officer.