# Public-Sector Data Science & Analytics Lead

**Company:** [AlphaHire](https://jobs.workable.com/companies/qTKMeatvbaN7e4oCC4V8kB.md)
**Location:** Remote
**Workplace:** remote

[Apply for this job](https://jobs.workable.com/view/629b1b7c-746d-4a09-abb7-4b55879b90a3)

## Description

AlphaGov is seeking a Public-Sector Data Science & Analytics Lead for project-based engagements with cities, counties, state agencies, transit/utility authorities, school systems, and related public employers.

You will design and deliver forecasting, data-quality, performance-measurement, and analytics-implementation work that produces decision-ready products for government clients. This is applied analytics consulting — not staff-augmentation coding, pure academic research, or product SaaS sales.

What you'll do:

\- Lead or co-lead public-sector analytics engagements (forecasting, performance measurement, data quality, dashboard/implementation support)

\- Frame analytic questions with domain experts and translate findings for executives and elected/appointed stakeholders

\- Build reproducible analyses using administrative and public datasets; document methods and limitations

\- Advise on data governance, quality controls, and sustainable handoff to agency staff

\- Contribute technical write-ups, scopes, and proposal content for AlphaGov pursuits

\- Coordinate with evaluation, LMI/workforce, and operations SMEs when scopes overlap

## Requirements

-   Required:  
    5+ years applied data science, analytics, or quantitative public-policy work (government, public consulting, or research-to-practice)  
    Demonstrated delivery of at least two public-sector or quasi-public analytic products (agency, your role, year)  
    Strong statistical literacy and clear writing for non-technical audiences  
    Ability to work project-based with AlphaGov as a named collaborator on proposals when permissioned  
      
    Nice to have:  
    Python and/or R plus modern BI (Power BI, Tableau, Looker)  
    Experience with government administrative data, privacy, or IRB-adjacent constraints  
    Transit, utility, workforce, or education analytics  
    Cloud data-warehouse familiarity (BigQuery, Snowflake, Redshift)