Data Scientist

Stock Group Analytics; Washington, Northern (District of Columbia, KY); Hybrid; USD 120,000 - 190,000; Full time

Job summary

Stock Group Analytics is seeking an experienced Data Scientist to apply advanced statistics and ML on Government data, delivering predictive insights, forecasts, and integrated dashboards. Collaborate with AI Engineers, Data Analysts and governance bodies to ensure quality and responsible AI practices.

Qualifications include a PhD and 7+ years of production ML experience. You will deploy models, perform trend analyses, and support data-driven decision making across operational systems and Power

Qualifications

• PhD in Data Science, Statistics, Mathematics, CS or related quantitative field (Master's with extensive experience considered)
• 7+ years of experience building and deploying predictive models in production environments
• Expert proficiency in Python and/or R for data science
• Strong knowledge of ML 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
• Familiarity with data visualization tools (Power BI, Tableau)

Responsibilities

• Build and deploy predictive models for operations (predictive maintenance, demand forecasting, anomaly detection)
• Perform statistical analysis and trend forecasting on historical data
• Develop ML models trained on Government 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

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