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
• Arc GIS
• 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.
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