Avantus Federal
Company Overview
We are a world-class team of professionals who deliver next generation technology and products in robotic and autonomous platforms, ground, soldier, and maritime systems in 50+ locations world-wide. Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR).
QinetiQ US’s dedicated experts in defense, aerospace, security, and related fields all work together to explore new ways of protecting the American Warfighter, Security Forces, and Allies. Being a part of QinetiQ US means being central to the safety and security of the world around us. Partnering with our customers, we help save lives; reduce risks to society; and maintain the global infrastructure on which we all depend.
Why Join QinetiQ US?
If you have the courage to take on a wide variety of complex challenges, then you will experience a unique working environment where innovative teams blend different perspectives, disciplines, and technologies to discover new ways of solving complex problems. In our diverse and inclusive environment, you can be authentic, feel valued, be respected, and realize your full potential. QinetiQ US will support you with workplace flexibility, a commitment to the health and well-being of you and your family and provide opportunities to work with a purpose. We are committed to supporting your success in both your professional and personal lives.
Position Overview QinetiQ US seeks an enthusiastic Junior Data Scientist to join a federal law enforcement agency client. This entry-level role provides an excellent opportunity to begin a career in data science while supporting the agency with data analysis and insights.
Working closely with senior team members, you will learn to utilize platforms such as Databricks, Qlik, Tableau, Oracle, ServiceNow, Microsoft Power Suite, Python programming, data visualization, and SQL to support data analysis for the Law Enforcement Lifecycle. This role offers extensive mentorship and training opportunities while contributing to mission-critical federal operations.
Responsibilities
Data Analysis & Learning
Learn to apply basic mathematical methods to analyze datasets using R or Python under senior guidance
Support data preparation, cleaning, and validation activities for agency systems
Assist with basic statistical analysis and data exploration tasks
Learn fundamental concepts of predictive modeling and discrete event simulation (DES)
Participate in training on multiple correspondence analysis (MCA), principal component analysis (PCA), and association rule mining
Assist in the professional and technical development of fellow staff
Responsibilities
Technology Platform Exposure
Gain hands-on experience with platforms including: Databricks, Qlik, Tableau, Oracle, ServiceNow, Microsoft Power Suite, Python, and SQL
Learn to perform basic queries and data extraction using SQL, MS Access, and MS Excel
Support senior team members with data processing and analysis tasks
Participate in training on High-Performance Computing (HPC) environments
Data Processing Support
Assist with basic data pipeline activities and data integration tasks
Learn to work with federal government data from various sources under supervision
Support data quality checks and validation processes
Help with extract, transform, load (ETL) operations for law enforcement data
Documentation & Reporting
Learn to create basic reports and visualizations using tools like RMarkdown or Jupyter Notebook
Assist in preparing data summaries and presentations for team review
Support documentation of analytical processes and findings
Practice communicating technical concepts to various audiences
Administrative Support
Participate in team meetings and training sessions
Assist with project documentation and tracking
Support ad-hoc data requests and analysis tasks
Help maintain organized data files and project materials
Professional Development
Participate in mentorship programs with senior data scientists
Attend training sessions on federal data requirements and security protocols
Learn about agency systems and law enforcement operations
Develop understanding of government data analysis standards and practices
Required Qualifications
Bachelor\'s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or related technical field
0-2 years of relevant experience (new graduates welcome)
Strong academic background in mathematics, statistics, or computer science
Desired Technical Skills
Basic proficiency in R or Python programming
Fundamental understanding of statistics and data analysis concepts
Familiarity with SQL and database concepts
Basic experience with data visualization tools
Understanding of Excel and basic data manipulation
Strong analytical and problem-solving skills
Security Requirements
Ability to obtain and maintain appropriate federal security clearance.
Background investigation required.
Must be U.S. citizen.
Preferred Qualifications
Educational Background
Coursework or projects involving data analysis, machine learning, or statistics
Experience with programming languages beyond basic requirements
Academic projects using real-world datasets
Understanding of research methodologies
Technical Exposure
Familiarity with any business intelligence tools (Tableau, Power BI, etc.)
Basic understanding of cloud computing platforms
Exposure to version control systems like GitHub
Understanding of data privacy and security concepts
Additional Experience
Internships or co-op experience in data analysis or related fields
Academic research experience involving data
Participation in data science competitions or projects
Volunteer work involving data analysis
Company EEO Statement Accessibility/Accommodation:
If because of a medical condition or disability you need a reasonable accommodation for any part of the employment process, please send an e-mail to staffing@us.QinetiQ.com or call (540) 658-2720 Opt. 4 and let us know the nature of your request and contact information.
QinetiQ US is an Equal Opportunity/Affirmative Action employer. All Qualified Applicants will receive equal consideration for employment without regard to race, age, color, religion, creed, sex, sexual orientation, gender identity, national origin, disability, or protected Veteran status.
#J-18808-Ljbffr
QinetiQ US’s dedicated experts in defense, aerospace, security, and related fields all work together to explore new ways of protecting the American Warfighter, Security Forces, and Allies. Being a part of QinetiQ US means being central to the safety and security of the world around us. Partnering with our customers, we help save lives; reduce risks to society; and maintain the global infrastructure on which we all depend.
Why Join QinetiQ US?
If you have the courage to take on a wide variety of complex challenges, then you will experience a unique working environment where innovative teams blend different perspectives, disciplines, and technologies to discover new ways of solving complex problems. In our diverse and inclusive environment, you can be authentic, feel valued, be respected, and realize your full potential. QinetiQ US will support you with workplace flexibility, a commitment to the health and well-being of you and your family and provide opportunities to work with a purpose. We are committed to supporting your success in both your professional and personal lives.
Position Overview QinetiQ US seeks an enthusiastic Junior Data Scientist to join a federal law enforcement agency client. This entry-level role provides an excellent opportunity to begin a career in data science while supporting the agency with data analysis and insights.
Working closely with senior team members, you will learn to utilize platforms such as Databricks, Qlik, Tableau, Oracle, ServiceNow, Microsoft Power Suite, Python programming, data visualization, and SQL to support data analysis for the Law Enforcement Lifecycle. This role offers extensive mentorship and training opportunities while contributing to mission-critical federal operations.
Responsibilities
Data Analysis & Learning
Learn to apply basic mathematical methods to analyze datasets using R or Python under senior guidance
Support data preparation, cleaning, and validation activities for agency systems
Assist with basic statistical analysis and data exploration tasks
Learn fundamental concepts of predictive modeling and discrete event simulation (DES)
Participate in training on multiple correspondence analysis (MCA), principal component analysis (PCA), and association rule mining
Assist in the professional and technical development of fellow staff
Responsibilities
Technology Platform Exposure
Gain hands-on experience with platforms including: Databricks, Qlik, Tableau, Oracle, ServiceNow, Microsoft Power Suite, Python, and SQL
Learn to perform basic queries and data extraction using SQL, MS Access, and MS Excel
Support senior team members with data processing and analysis tasks
Participate in training on High-Performance Computing (HPC) environments
Data Processing Support
Assist with basic data pipeline activities and data integration tasks
Learn to work with federal government data from various sources under supervision
Support data quality checks and validation processes
Help with extract, transform, load (ETL) operations for law enforcement data
Documentation & Reporting
Learn to create basic reports and visualizations using tools like RMarkdown or Jupyter Notebook
Assist in preparing data summaries and presentations for team review
Support documentation of analytical processes and findings
Practice communicating technical concepts to various audiences
Administrative Support
Participate in team meetings and training sessions
Assist with project documentation and tracking
Support ad-hoc data requests and analysis tasks
Help maintain organized data files and project materials
Professional Development
Participate in mentorship programs with senior data scientists
Attend training sessions on federal data requirements and security protocols
Learn about agency systems and law enforcement operations
Develop understanding of government data analysis standards and practices
Required Qualifications
Bachelor\'s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or related technical field
0-2 years of relevant experience (new graduates welcome)
Strong academic background in mathematics, statistics, or computer science
Desired Technical Skills
Basic proficiency in R or Python programming
Fundamental understanding of statistics and data analysis concepts
Familiarity with SQL and database concepts
Basic experience with data visualization tools
Understanding of Excel and basic data manipulation
Strong analytical and problem-solving skills
Security Requirements
Ability to obtain and maintain appropriate federal security clearance.
Background investigation required.
Must be U.S. citizen.
Preferred Qualifications
Educational Background
Coursework or projects involving data analysis, machine learning, or statistics
Experience with programming languages beyond basic requirements
Academic projects using real-world datasets
Understanding of research methodologies
Technical Exposure
Familiarity with any business intelligence tools (Tableau, Power BI, etc.)
Basic understanding of cloud computing platforms
Exposure to version control systems like GitHub
Understanding of data privacy and security concepts
Additional Experience
Internships or co-op experience in data analysis or related fields
Academic research experience involving data
Participation in data science competitions or projects
Volunteer work involving data analysis
Company EEO Statement Accessibility/Accommodation:
If because of a medical condition or disability you need a reasonable accommodation for any part of the employment process, please send an e-mail to staffing@us.QinetiQ.com or call (540) 658-2720 Opt. 4 and let us know the nature of your request and contact information.
QinetiQ US is an Equal Opportunity/Affirmative Action employer. All Qualified Applicants will receive equal consideration for employment without regard to race, age, color, religion, creed, sex, sexual orientation, gender identity, national origin, disability, or protected Veteran status.
#J-18808-Ljbffr