Data Scientist

ISF Inc seeks an independent contractor to provide quantitative QA review and advisory support for an applied public health predictive modeling pipeline.

Responsibilities

• Read and evaluate the project’s technical framework document to assess internal consistency of the model specification, appropriateness of assumptions, and correct implementation of the described approach.
• Flag methodological concerns, specification errors, or mismatches between described methods and standard practice in Bayesian spatial modeling or public health surveillance.
• Validate that model outputs are plausible, internally consistent, and correctly reported in tables and figures, including:
  • latent population estimates
  • detection probabilities
  • geographic risk scores
  • treatment effect estimates
  • convergence diagnostics
  • scenario projections
• Verify that numerical values in the technical document match underlying model output files.
• Confirm arithmetic correctness for rates, percentages, aggregations, and credible intervals.
• Re-review updated sections of the technical deliverable to confirm numerical values, statistical summaries, table entries, and methodological descriptions reflect the underlying analytical work.
• Identify mischaracterizations, ambiguous descriptions, or documentation gaps where outputs do not match.
• Provide written review comments for the lead scientist to address.
• After data refreshes of the Azure-hosted decision-support tool, spot-check displayed values (county-level counts, rates, projections, and KPI figures) against source model output files.
• Provide time range estimates for requested QA outputs to the Principal within 24 hours of tasking.
• Send weekly updates to the Principal regarding work completed.
• Provide objective feedback on the predictive model and outputs to the Principal, including advising on future scoping with the client as appropriate.

Requirements

• Ph.D. in biostatistics, statistics, health data science, epidemiology, or a closely related quantitative field.
• Experience translating highly technical concepts with simplicity and accuracy for non-specialist audiences.
• Experience estimating time required to complete tasks.
• Experience advising leadership on technical processes, outputs, and hours needed to complete scope.
• Must be proficient in R, Azure, Azure Databricks, and Claude Code.
• Must currently hold, or have the ability to obtain, CITI certification to access restricted data.
• Professional client-service capability: translate complex findings for non-specialist audiences, manage your own time and scope reliably, and work effectively with institutional clients.
• Experience advising or presenting to external clients, government agencies, or institutional stakeholders is vital.

Tech Stack

• R
• Azure
• Azure Databricks
• Claude Code
• SHAP
• MCMC
• RShiny
• Git
• ArcGIS
• R packages (CAR/ICAR)

Engagement

• Engagement type: Independent Contractor (1099)
• Core function: QA review of model outputs and documentation; primary backup support for lead data scientist
• Hours: approximately 10–20 hours per month; as-needed basis; opportunity to grow into longer term engagement
• Availability: occasional 1-hour meetings between 9 AM–5 PM ET (particularly during onboarding)
• Deadline management: ability to meet internal deadlines as agreed with the Principal
• Reports to: Principal, Management Consulting

Compensation

• USD 75–160 per hour based on qualifications
• Billed monthly based on hours worked

Data Access, IRB Compliance & CITI Training

• Access to project data requires current CITI Program certification in Human Subjects Research.
• If you do not have current certification, you must complete CITI training (self-paced, available at citiprogram.org) before data access is granted.
• Additional data use agreement or IRB protocol requirements will be communicated at onboarding.

Independent Contractor Status & Confidentiality

• This is a 1099 independent contractor engagement; contractor is responsible for their own taxes and benefits.
• No employment relationship is created or implied.
• Contractor will have access to sensitive public health surveillance data governed by applicable data use agreements and confidentiality obligations.

How to Apply

• Submit: current CV or resume highlighting consulting and advisory experience alongside your quantitative training.
• Submit: a brief note (half page or less) describing your experience advising public sector or academic clients on quantitative work.
• Applications reviewed on a rolling basis.