Product Architect (Data Scientist)
Job Category: Information Technology
Time Type: Full time
Minimum Clearance Required to Start: None
Employee Type: Regular
Percentage of Travel Required: Up to 10%
Type of Travel: Local

CACI is currently looking for a motivated, career and customer-oriented SME level Data Scientist and Product Architect with Agile methodology experience to join our Customs and Border Protection (CBP) Land Border Integration (LBI) Integrated Traveler Initiative 2.1 (ITI2.1) team in Northern Virginia! Join this passionate team of industry-leading individuals supporting the best practices in Agile Software Development and hardware integration for the Department of Homeland Security (DHS).
As a member of the ITI2.1 Team, you will support the men and women charged with safeguarding the American people and enhancing the Nation’s safety, security, and prosperity. CBP Officers and Border Patrol agents are on the front lines, every day, protecting our national security by combining customs, immigration, border security, and agricultural protection into one coordinated and supportive activity.
CACI agile programs thrive in a culture of innovation and are constantly seeking individuals who can bring creative ideas to solve complex problems, both technical and procedural at the team and portfolio levels. The ability to be adaptable and to work constructively with a technically diverse and geographically separated team is crucial.

The Data Science subject matter expert will manage and use data to design data-driven predictive maintenance model, infer and recommend business decision, and conduct root cause (causality) analysis, support IoT device signal analytics, and trend analysis for ITI2.1 requirement. We are looking for experienced engineers who know how to solve complex big data problems, work with algorithms, analyze big data and can run end-to-end data analytical pipeline.

• Develop an understanding of the customer’s data environment through data profiling and statistical analyses
• Execute complex SQL queries
• Design and development of complex large scale OLTP systems
• Obtain, scrub, explore, model and interpret data currently stored in Oracle various types of databases - using SQL and other data mining tools
• Perform statistical analysis and tune using test results
• Study appropriate datasets and transform data science prototypes
• Research and implement appropriate machine learning algorithms and tools and develop machine learning applications according to requirements
• Train data-driven learning model.
• Maintain and work with data pipeline that transfers and processes large scale of heterogenous structural/non-structural data using Spark, Scala, Python, Apache Kafka, TensorFlow, PyTorch, and/or other data analytic tools
• Design, build and support pipelines of data transformation, conversion, validation
• Build data manipulation, processing, and data visualization tools and share these tools across the team.
• Leverage the statistical and computational knowledge to build algorithms for reporting.
• Apply data analysis, data mining and data engineering to present data clearly and develop experiments
• Ensure high-quality data and understand how data is generated out experimental design and how these experiments can produce actionable, trustworthy conclusions.
• Assist senior management in making key business decisions.
• Work with development teams to build tools for data logging and repeatable data tasks that will accelerate and automate data scientist duties

The Data Science subject matter expert will manage and use data to design data-driven predictive maintenance model, infer and recommend business decision, and conduct root cause (causality) analysis, support IoT device signal analytics, and trend analysis for ITI2.1 requirement. We are looking for experienced engineers who know how to solve complex big data problems, work with algorithms, analyze big data and can run end-to-end data analytical pipeline.

• Develop an understanding of the customer’s data environment through data profiling and statistical analyses
• Execute complex SQL queries
• Design and development of complex large scale OLTP systems
• Obtain, scrub, explore, model and interpret data currently stored in Oracle various types of databases - using SQL and other data mining tools
• Perform statistical analysis and tune using test results
• Study appropriate datasets and transform data science prototypes
• Research and implement appropriate machine learning algorithms and tools and develop machine learning applications according to requirements
• Train data-driven learning model.
• Maintain and work with data pipeline that transfers and processes large scale of heterogenous structural/non-structural data using Spark, Scala, Python, Apache Kafka, TensorFlow, PyTorch, and/or other data analytic tools
• Design, build and support pipelines of data transformation, conversion, validation
• Build data manipulation, processing, and data visualization tools and share these tools across the team.
• Leverage the statistical and computational knowledge to build algorithms for reporting.
• Apply data analysis, data mining and data engineering to present data clearly and develop experiments
• Ensure high-quality data and understand how data is generated out experimental design and how these experiments can produce actionable, trustworthy conclusions.
• Assist senior management in making key business decisions.
• Work with development teams to build tools for data logging and repeatable data tasks that will accelerate and automate data scientist duties.