Public-Sector Data Science Lead

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead or co-lead analytics projects in the public sector that involve forecasting, performance measurement, data quality, dashboards, and support for implementation.

• Collaborate with domain experts to frame analytic inquiries and effectively communicate findings to executives and appointed or elected stakeholders.

• Develop reproducible analyses utilizing both administrative and public datasets.

• Document analytical methodologies and their limitations.

• Provide guidance on data governance, quality control measures, and ensure a sustainable transition to agency personnel.

• Contribute to technical documentation, project scopes, and proposal materials for AlphaGov initiatives.

• Work alongside subject-matter experts in evaluation, labor market information/workforce, and operations when project scopes intersect.

⛳️ Requirements

• A minimum of 5 years of experience in applied data science, analytics, or quantitative public-policy roles (including government, public consulting, or transitioning research into practice).

• Proven track record of delivering at least two analytic products for the public or quasi-public sector (including details like agency, your role, and year).

• Strong statistical understanding and the ability to write clearly for non-technical audiences.

• Capacity to work on a project basis with AlphaGov as a recognized collaborator on proposals when authorized.

• Proficiency in Python and/or R along with modern business intelligence tools (such as Power BI, Tableau, or Looker) is a plus.

• Familiarity with government administrative data, privacy considerations, or constraints related to Institutional Review Boards (IRB) is advantageous.

• Experience in analytics related to transit, utilities, workforce, or education is preferred.

• Knowledge of cloud data warehousing solutions (like BigQuery, Snowflake, or Redshift) is a plus.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Opportunities for professional development and continuous learning.

• Flexible work arrangements to promote work-life balance.

• Collaborative and inclusive work environment.