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Government Data Analytics Manager Jobs (NOW HIRING)

Stock Group Analytics

$150 - $200/hr

Perform statistical analysis and trend forecasting on historical data * Develop machine learning models trained on Government's data for specific use cases * Integrate predictive analytics into Power ...

Xe Careers

Revenue Data & Analytics Manager

Irvine, CA · On-site

$130K - $160K/yr

Description Revenue Data & Analytics Manager Location: Irvine, CA Reports to: Head of Revenue Operations About the Role Revenue Operations is a newly formed function at Xe as we scale our growth ...

AIG

Data Analytics, Manager, P&C Insurance

New York, NY

$120K - $150K/yr

Join us as a Data Analytics, Manager, Commercial Lines to play your part in that transformation. It's an opportunity to grow your skills and experience as a valued member of the team. Make Your Mark:

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Government Data Analytics Manager information

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$97.1K

$172K

How much do government data analytics manager jobs pay per year?

As of Sep 9, 2026, the average yearly pay for government data analytics manager in the United States is $97,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $125,500.00 per year, depending on experience, location, and employer.

What are popular job titles related to Government Data Analytics Manager jobs?

For Government Data Analytics Manager jobs, the most frequently searched job titles are:

Infographic showing various Government Data Analytics Manager job openings in the United States as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $97,145 per year, or $46.7 per hour.

Data Scientist

On-site

Stock Group Analytics
IT Services • 1 - 10 employees
Learn more about Stock Group Analyticsexternal

$150 - $200/hr

Other

Posted 10 days ago

Job description

Position Summary

The Data Scientist is responsible for applying advanced statistical and machine learning techniques to Government’s data to generate predictive insights, develop forecasting models, and support data-driven decision-making. This role works closely with AI Engineers and Data Analysts to integrate predictive capabilities into dashboards and operational systems.

Key Responsibilities
  • Build and deploy predictive models for operations (e.g., predictive maintenance, demand forecasting, anomaly detection)
  • Perform statistical analysis and trend forecasting on historical data
  • Develop machine learning models trained on Government's data for specific use cases
  • Integrate predictive analytics into Power BI dashboards and operational systems
  • Design and implement AI-assisted data quality checks including ML-based anomaly detection
  • Conduct exploratory data analysis to identify patterns and insights
  • Evaluate model performance and implement continuous improvement processes
  • Collaborate with Data Engineers on data pipeline requirements for ML workflows
  • Document model methodologies, assumptions, and performance metrics
  • Present findings and recommendations to technical and non-technical stakeholders
  • Support AI Governance Board with model performance reporting and bias assessments
Required Qualifications
  • Education: Ph.D. in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field (Master's with extensive experience considered)
  • Experience: 7+ years of experience building and deploying predictive models in production environments
  • Technical Skills:
    • Expert proficiency in Python and/or R for data science
    • Strong knowledge of machine learning algorithms and statistical techniques
    • Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch)
    • Proficiency in SQL and database querying
    • Experience with cloud data platforms (Azure ML, AWS, GCP)
    • Knowledge of time series forecasting and anomaly detection techniques
    • Familiarity with data visualization tools (Power BI, Tableau)
Preferred Qualifications
  • Domain knowledge in manufacturing analytics, quality control, or production operations
  • Experience in federal government data science programs
  • Knowledge of Responsible AI principles and model governance
  • Experience with Azure Machine Learning and Azure Synapse Analytics
  • Publications or demonstrated expertise in applied machine learning
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