QinetiQ US seeks to improve data quality across agency systems for a federal law enforcement agency client by collecting, analyzing, and interpreting law enforcement data to drive informed operational decisions
Requirements
- Demonstrated proficiency in Python, R, and SQL for data analysis and automation
- Experience with Databricks, Oracle (OBIEE/OAS), and UiPath or similar automation platforms
- Proven ability to work with VBA and database management systems
- Experience implementing the Data Analysis Epicycle and performing statistical analysis techniques (MCA, PCA, association rule mining)
- Skilled in producing executive-level reports using RMarkdown, Jupyter Notebook, or similar tools
- Experience with dashboard development and data visualization for law enforcement operations
- Familiarity with federal data governance and compliance requirements
Responsibilities
- Apply appropriate mathematical methods to statistically analyze agency data quality issues using Python, R, and SQL
- Create tools for identifying, monitoring, and implementing data quality solutions utilizing Databricks, Oracle (OBIEE/OAS), UiPath, VBA, Python, R, and SQL
- Develop algorithms for automated data quality error remediation and validation processes
- Ensure accuracy of data uploaded to agency systems
- Conceptualize, plan, design, and develop machine learning algorithms for data quality optimization and automated error detection
- Implement predictive models to identify potential data quality issues before they impact operations
- Perform multiple correspondence analysis (MCA), principal component analysis (PCA), and association rule mining on law enforcement datasets
Other
- Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, Information Systems, or related technical field
- Minimum 10 years of relevant data science and analytics experience
- Ability to obtain and maintain appropriate federal security clearance
- Background investigation required
- Must be U.S. citizen
- Experienced working with federal law enforcement or homeland security categorical data from flat files, data warehouses, and external sources
