QinetiQ US
Overview
QinetiQ US seeks a highly skilled Senior Data Scientist to support a federal law enforcement agency client. This role is responsible for collecting, analyzing, and interpreting law enforcement data to drive informed operational decisions and improve data quality across agency systems. Your expertise in utilizing Databricks, Oracle (OBIEE/OAS), UiPath, Python programming, SQL, and data visualization will be crucial in identifying data quality issues, developing automated solutions, and providing valuable recommendations to federal stakeholders. Responsibilities
Data Quality Analysis & Engineering 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 Advanced Analytics & Automation 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 Develop automation solutions using emerging tools including UiPath for repetitive data quality tasks Reporting & Communication Produce executive-level summary reports and briefings of data quality analysis results using RMarkdown, Jupyter Notebook, or equivalent tools Create comprehensive audit reports for agency Dashboards ensuring accuracy, completeness, and usability standards Develop data visualizations and dashboards for federal stakeholders to monitor data quality metrics Present complex technical findings to federal staff and law enforcement personnel in accessible language Technical Support & Collaboration Provide ad hoc after-hours support for emergency taskings requiring advanced analytics Collaborate with federal staff to identify and resolve historical data errors in law enforcement systems Support development of training materials and system documentation for data quality processes Serve as technical subject matter expert for cross-unit data quality initiatives Assist in the professional and technical development of fellow staff Required Qualifications
Education & Experience
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 Technical Requirements
Demonstrated proficiency in R and Python, and familiarity with other leading statistical and data analytical software and frameworks, including Databricks and Qlik Proven ability to produce executive level summary reports/briefings using RMarkdown or Jupyter Notebook Experience implementing the Data Analysis Epicycle and skilled in performing multiple correspondence analysis (MCA), PCA, and association rule mining Experience working with federal government categorical data from flat files, data warehouses, and external/academic sources Government Experience
Experienced working with federal law enforcement or homeland security categorical data from flat files, data warehouses, and external sources Direct experience interfacing with federal agencies as an employee or contractor, preferably at DHS Demonstrated experience supporting data quality initiatives in government systems Must have experience explaining complex technical concepts to federal government clients Security Requirements
Ability to obtain and maintain appropriate federal security clearance. Background investigation required. Must be U.S. citizen. Specialized Experience & Preferred Qualifications
Experience supporting federal homeland security initiatives Background in immigration enforcement, law enforcement operations, or related domains Experience with DHS systems and processes Familiarity with law enforcement operational requirements and data structures Professional Certifications (Optional)
Advanced Data Science: Certified Senior Data Scientist (CSDS); Certified Analytics Professional (CAP) Machine Learning and AI: Microsoft Azure AI Engineer Associate; Azure Data Scientist Associate; AWS Certified Machine Learning – Specialty; Google Professional Machine Learning Engineer; Databricks certified professional Additional: ArcGIS and geospatial analysis; ServiceNow; Microsoft Power Suite (Power BI, Power Apps, Power Automate); High-Performance Computing; GitHub and collaborative development practices Security & Accessibility
Accessibility/Accommodation: If you need a reasonable accommodation for any part of the employment process, email staffing@us.QinetiQ.com or call (540) 658-2720 Opt. 4 QinetiQ US is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive equal consideration without regard to race, age, color, religion, creed, sex, sexual orientation, gender identity, national origin, disability, or protected Veteran status. Other Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Defense and Space Manufacturing Referrals increase your chances of interviewing at QinetiQ US. This summary reflects the position as described in the source material.
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QinetiQ US seeks a highly skilled Senior Data Scientist to support a federal law enforcement agency client. This role is responsible for collecting, analyzing, and interpreting law enforcement data to drive informed operational decisions and improve data quality across agency systems. Your expertise in utilizing Databricks, Oracle (OBIEE/OAS), UiPath, Python programming, SQL, and data visualization will be crucial in identifying data quality issues, developing automated solutions, and providing valuable recommendations to federal stakeholders. Responsibilities
Data Quality Analysis & Engineering 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 Advanced Analytics & Automation 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 Develop automation solutions using emerging tools including UiPath for repetitive data quality tasks Reporting & Communication Produce executive-level summary reports and briefings of data quality analysis results using RMarkdown, Jupyter Notebook, or equivalent tools Create comprehensive audit reports for agency Dashboards ensuring accuracy, completeness, and usability standards Develop data visualizations and dashboards for federal stakeholders to monitor data quality metrics Present complex technical findings to federal staff and law enforcement personnel in accessible language Technical Support & Collaboration Provide ad hoc after-hours support for emergency taskings requiring advanced analytics Collaborate with federal staff to identify and resolve historical data errors in law enforcement systems Support development of training materials and system documentation for data quality processes Serve as technical subject matter expert for cross-unit data quality initiatives Assist in the professional and technical development of fellow staff Required Qualifications
Education & Experience
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 Technical Requirements
Demonstrated proficiency in R and Python, and familiarity with other leading statistical and data analytical software and frameworks, including Databricks and Qlik Proven ability to produce executive level summary reports/briefings using RMarkdown or Jupyter Notebook Experience implementing the Data Analysis Epicycle and skilled in performing multiple correspondence analysis (MCA), PCA, and association rule mining Experience working with federal government categorical data from flat files, data warehouses, and external/academic sources Government Experience
Experienced working with federal law enforcement or homeland security categorical data from flat files, data warehouses, and external sources Direct experience interfacing with federal agencies as an employee or contractor, preferably at DHS Demonstrated experience supporting data quality initiatives in government systems Must have experience explaining complex technical concepts to federal government clients Security Requirements
Ability to obtain and maintain appropriate federal security clearance. Background investigation required. Must be U.S. citizen. Specialized Experience & Preferred Qualifications
Experience supporting federal homeland security initiatives Background in immigration enforcement, law enforcement operations, or related domains Experience with DHS systems and processes Familiarity with law enforcement operational requirements and data structures Professional Certifications (Optional)
Advanced Data Science: Certified Senior Data Scientist (CSDS); Certified Analytics Professional (CAP) Machine Learning and AI: Microsoft Azure AI Engineer Associate; Azure Data Scientist Associate; AWS Certified Machine Learning – Specialty; Google Professional Machine Learning Engineer; Databricks certified professional Additional: ArcGIS and geospatial analysis; ServiceNow; Microsoft Power Suite (Power BI, Power Apps, Power Automate); High-Performance Computing; GitHub and collaborative development practices Security & Accessibility
Accessibility/Accommodation: If you need a reasonable accommodation for any part of the employment process, email staffing@us.QinetiQ.com or call (540) 658-2720 Opt. 4 QinetiQ US is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive equal consideration without regard to race, age, color, religion, creed, sex, sexual orientation, gender identity, national origin, disability, or protected Veteran status. Other Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Defense and Space Manufacturing Referrals increase your chances of interviewing at QinetiQ US. This summary reflects the position as described in the source material.
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