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Description
Leidos, a global technology leader, is seeking Data Scientist for our UniCORN program, supporting the United States Air Force in geographically distributed intelligence operations.
UniCORN, developed by Leidos, revolutionizes ISR operations by enabling quick and effective planning, collection, analysis, and production of intelligence. This highly intuitive workflow orchestration system optimizes ISR problem sets, providing enterprise and site-level intelligence production management services for global ISR operations.
We are seeking a talented and motivated Data Scientist to join our team in the design and implementation of UNICORN, an innovative message broker system. This role requires a unique blend of data science expertise and software development skills to analyze large datasets, develop predictive models, and optimize message routing. As a Data Scientist at UNICORN, you will collaborate closely with cross-functional teams to ensure the system’s efficiency, reliability, and scalability. If you are passionate about leveraging data to drive real-time decision-making and enhance system performance, we encourage you to apply.
Join Leidos in our mission to enhance global security and efficiency through technology and innovation. Be part of a team that champions Integrity, Inclusion, Innovation, Agility, Collaboration, and Commitment. If you’re ready to take charge of critical configurations and support essential deployments, apply now to join Leidos as a Data Scientist for the UNICORN program!
Primary Responsibilities
Data Analysis and Insight Generation:
• Analyze and interpret large datasets to identify trends, patterns, and anomalies that can enhance message routing and processing.
• Develop dashboards and visualizations to communicate insights to stakeholders.
Predictive Modeling and Optimization:
• Build and refine predictive models to optimize message delivery times and ensure high reliability.
• Use machine learning techniques to continuously improve message broker performance.
Software Development and Integration:
• Collaborate with software developers to integrate data models and algorithms into the UNICORN message broker system.
• Write efficient, scalable, and maintainable code using Python, Java, and other relevant programming languages.
System Design and Architecture:
• Contribute to the design and development of system architecture with a focus on data flow, storage, and processing.
• Ensure that the system architecture supports both real-time message brokering and historical data maintenance.
Historical Data Management:
• Implement and manage databases to store historical message data securely and efficiently.
• Develop strategies for data retention, archival, and retrieval to support future machine learning and AI initiatives.
Machine Learning and AI Development:
• Prepare and process historical data for machine learning applications.
• Develop and deploy machine learning models to extract actionable insights from historical data.
• Continuously evaluate and improve the accuracy and performance of machine learning models.
Cross-functional Collaboration:
• Work closely with cross-functional teams, including developers, field engineers, and DevOps engineers, to ensure seamless integration and operation of the message broker system.
• Participate in project planning, progress reviews, and technical discussions to align data science activities with overall project goals.
Quality Assurance and Testing:
• Develop and implement testing strategies to validate the performance and accuracy of data models and algorithms.
• Identify and resolve data quality issues to maintain the integrity of the system.
Documentation and Reporting:
• Document data science processes, models, and algorithms for future reference and reproducibility.
• Generate reports and presentations to communicate findings and progress to stakeholders.
Continuous Learning and Improvement:
• Stay updated with the latest trends and advancements in data science, machine learning, and AI.
• Apply new knowledge to improve the UNICORN system and drive innovation.
Basic Qualifications
Education and Experience:
• Degree in Data Science, Computer Science, Systems Engineering, Information Engineering, or a related field.:
• Bachelor’s Degree: 0 – 2 years of experience required
• Master’s Degree: 0 – 2 years of experience required
• No clearance required to start, but the ability to obtain up to a TS/SCI is required.
• Proficiency in programming languages such as Python, Java, and R.
• Experience with data analysis tools and libraries (e.g., pandas, NumPy, scikit-learn).
• Familiarity with database systems and SQL for managing and querying large datasets.
• Knowledge of machine learning algorithms and frameworks.
• Understanding of data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Strong foundation in mathematics and statistics, including linear algebra, probability, and statistical inference.
• Ability to perform data extraction, cleaning, and preprocessing.
• Experience in building and validating predictive models.
• Experience in software development, including writing and testing code.
• Familiarity with version control systems such as Git.
• Understanding of software development best practices, including code reviews, testing, and documentation.
• Ability to analyze complex problems, identify patterns, and propose data-driven solutions.
• Experience in applying data science techniques to real-world problems.
• Strong verbal and written communication skills to convey technical concepts to non-technical stakeholders.
• Ability to create clear and concise documentation and reports.
• Ability to work effectively in a collaborative, cross-functional team environment.
• Experience working on projects with diverse teams, including developers, engineers, and business stakeholders.
• Willingness to stay updated with the latest developments in data science, machine learning, and AI.
• Openness to learning new tools, techniques, and technologies as needed for the project.
Preferred Qualifications
• Relevant internship or professional experience in data science, analytics, or a related field.
• Demonstrated experience in handling large datasets and performing data-driven analysis.
Original Posting Date:
2024-07-30
While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range:
Pay Range $53,950.00 – $97,525.00
The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
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