Biostatistician - Advanced Modeling & Public Health Analytics

Description

Core duties include designing and executing complex statistical analyses such as time‑series, segmented regression, hierarchical and longitudinal models, as well as advanced techniques like factor analysis, structural equation modeling, and zero‑inflated negative binomial models. The incumbent will also develop interactive dashboards using R Shiny and Python, and produce manuscripts, reports, and presentations for peer‑review and clearance processes. Collaboration with multidisciplinary teams ensures findings are interpreted and translated into actionable insights while maintaining compliance with federal data governance standards.

• Design and implement advanced statistical analyses (time series, segmented regression, hierarchical, longitudinal, factor analysis, SEM, zero‑inflated models).
• Develop interactive dashboards and analytic tools using R Shiny and Python.
• Prepare manuscripts, reports, and presentations for peer‑reviewed publications and clearance processes.
• Collaborate with multidisciplinary teams to interpret results and provide actionable insights while ensuring compliance with federal data governance.
• Utilize R, SAS, Python (Pandas, NumPy, Scikit‑learn) and SQL for data manipulation, modeling, and visualization.
• Apply Bayesian and other advanced statistical modeling techniques.
• Work independently and design analyses based on research questions and data types.
• Build automated, reproducible workflows using R Markdown and version control (GitHub).

Requirements

The Biostatistician role supports public health agencies and life sciences projects, delivering advanced statistical modeling and analytics for federal and private clients. The position demands rigorous scientific methods, strong programming, and academic writing capabilities. Travel up to 10% may be required and a public trust clearance is necessary.

Candidates must hold a master’s degree and have at least three years of industry experience. Proficiency in R, SAS, Python (including Pandas, NumPy, Scikit‑learn) and SQL is required, along with demonstrated expertise in time‑series, Bayesian, and other advanced statistical modeling techniques. Strong academic writing, independent analytical design, and excellent communication and collaboration skills are essential, and the role is hybrid‑based in Atlanta, GA.

Preferred attributes include a PhD, experience with hierarchical, longitudinal and structural equation modeling, and familiarity with public‑health, real‑world and open‑source datasets. Experience building automated workflows with R Markdown, version control (GitHub), and platforms such as Databricks or Snowflake is valued, as is prior consulting experience.

• Demonstrate strong academic writing and experience with peer‑review and clearance procedures.
• Hold a master’s degree and minimum three years of industry experience.
• Preferably possess a PhD and experience with hierarchical, longitudinal, and structural equation modeling.
• Familiarity with public‑health, real‑world, and open‑source datasets.
• Experience with Databricks or Snowflake for large‑scale data processing.
• Prior consulting experience is a plus.

Benefits

Guidehouse offers a competitive total‑rewards package that includes medical, dental, vision, life and disability insurance, flexible paid time off, parental leave, 401(k), tuition reimbursement, and various professional development resources. Additional perks comprise discretionary bonuses, employee referral programs, corporate‑sponsored events, emergency childcare, and mobility stipends.

• Receive competitive compensation, flexible benefits, medical/dental/vision coverage, 401(k), tuition reimbursement, and professional development opportunities.
• Access discretionary variable incentive bonus, parental leave, adoption assistance, and employee referral program.
• Benefit from emergency backup childcare, mobility stipend, and corporate‑sponsored community events.

Training + Development

Interview process

Visa Sponsorship

Security clearance