Dataverse/Data Science Lead

Location: Remote within the United States; job locations include US-Remote and Washington, DC. U.S. citizenship and the ability to obtain a CBP Background Investigation are required; active CBP BI is preferred. The role requires 20% travel, including possible travel to remote and rugged areas.

Salary: $111,209–$180,317 annually.

Company

hirify.global supports the DHS Customs and Border Protection Program Management Office through mission-focused technology, analytics, and research services.

What you will do

• Lead analytical strategy for complex operational, workflow, technology, and programmatic questions aligned with customer priorities.
• Serve as the subject-matter expert for Microsoft Dataverse data structures, data management, analytical use cases, and integrations with reporting, automation, and data-science solutions.
• Assess data readiness and design reporting-ready Dataverse models, tables, relationships, transformations, validation rules, business logic, and analytical pipelines.
• Develop, review, and apply statistical models, machine-learning methods, predictive analytics, exploratory analyses, and AI or large-language-model evaluations.
• Translate analytical findings, uncertainty, bias, assumptions, data-quality issues, and limitations into actionable products for technical, operational, clinical, and executive stakeholders.
• Establish analytical governance and reusable standards while coordinating with data engineering, platform, application-development, Power Platform, data-owner, and governance stakeholders.

Requirements

• Master’s degree or higher in statistics, data science, operations research, public health, computer science, engineering, mathematics, or another related quantitative discipline.
• At least 9 years of progressive experience in applied data science, advanced analytics, statistical analysis, data engineering, or related analytical roles, including experience in federal health, healthcare, regulated-data environments, enterprise modernization, or similarly complex mission-driven organizations.
• Experience leading complex analytical efforts from problem definition through data assessment, analysis, validation, interpretation, and communication to technical and nontechnical stakeholders.
• Strong hands-on experience with Python and SQL for developing, testing, validating, and troubleshooting analytical workflows, data transformations, statistical models, and machine-learning solutions.
• Experience designing and assessing data models, data pipelines, data-quality controls, validation logic, data lineage, authoritative data sources, and reporting-ready datasets.
• Experience with advanced analytical methods such as predictive modeling, time-series analysis, causal inference, natural-language processing, machine learning, generative AI, or large-language-model evaluation.
• Experience with modern data, analytics, and visualization platforms, including Microsoft Dataverse, Databricks, Snowflake, Power BI, Azure, AWS, Google Cloud Platform, or comparable technologies.
• Ability to clearly communicate analytical methods, results, uncertainty, assumptions, bias, data-quality concerns, and limitations to leadership and decision-makers.
• Experience applying analytical standards for reproducibility, peer review, documentation, version control, quality assurance, validation, and responsible use of data and AI, plus technical leadership through mentoring, peer reviews, reusable standards, or complex analytical workstreams.

Nice to have

• Doctoral degree in a related quantitative discipline.
• Experience in healthcare, federal health, clinical analytics, public health, operations research, or other domains where data context and quality affect operational or programmatic decisions.
• Experience operationalizing analytics or machine-learning solutions through repeatable pipelines, model monitoring, MLOps, model lifecycle management, or production-engineering collaboration.
• Experience designing, implementing, or evaluating NLP, generative AI, or large-language-model solutions, including error analysis, bias or fairness assessment, and responsible-use considerations.
• Experience with Dataverse and Microsoft Power Platform, including table design, relationships, security roles, integrations, data management, reporting, and Power BI analytics.
• Advanced certifications in cloud machine learning, data science, analytics, data engineering, Databricks, Azure, AWS, Google Cloud Platform, Power Platform, or comparable technologies.
• Recognized technical leadership through publications, conference presentations, internal standards, training development, mentoring, peer-review leadership, or enterprise-scale analytical initiatives.

Culture & Benefits

• Remote work within the United States with 20% travel, including possible travel to remote and rugged areas.
• Work on mission-critical national security and border-protection challenges for DHS CBP.
• Collaborate across program, operational, technical, evaluation, data-governance, engineering, and platform functions.