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Stock Group Analytics

Data Scientist

washington, DC

Check who can apply and the requirements below before continuing.

About this opportunity

Stock Group Analytics lists this Data Scientist opportunity in washington, District of Columbia. Review the employer’s description below for duties, qualifications and application requirements.

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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Worksite address

washington, DC, 20022, US

Who can apply

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