CACI International Predictive Modeling Analyst Senior in Norfolk, Virginia
Predictive Modeling Analyst Senior
Job Category: Information Technology
Time Type: Full time
Minimum Clearance Required to Start: Secret
Employee Type: Regular
Percentage of Travel Required: Up to 25%
Type of Travel: Continental US
Must be willing to work onsite in Norfolk, Virginia. Applicants with experience as a Data Scientist/Data Analyst highly preferred.
What You’ll Get to Do:
Responsible for maintaining knowledge of online analytical processing (OLAP) tools.
Gathers analytical requirements working with subject management experts.
Develops data frameworks for data analysis to support end-user data discovery.
Designs and develops data models that optimize analytical reporting performance.
Develops data extraction, transformation, cleansing, and loading processes between transactional and analytical systems.
Builds reports, dashboards, and OLAP databases to support end-user reporting and information requirements.
Performs statistical analyses on data and predictive forecasting.
Analyzes and interprets results using statistical techniques. Interpret trends or patterns in complex data sets to their projects, and create interactive experiences that engage users.
More About the Role:
Review Government Furnished Information.
Review all training requirements from the Solution Architects.
Support design meetings with Software Developers, Solution Architects, Software Engineers and UI Engineers.
Work in a fast, dynamic environment.
You’ll Bring These Qualifications:
BA/BS with 5-7 years of data analysis experience.
Management experience leading teams of 3 or more team members.
Proficiency in languages for data manipulation and statistical analysis (SQL, SAS, MATLAB, R, Python, etc.).
Should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power Bl) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
Experience staying updated on industry best practices and emerging trends in data science and modeling.
These Qualifications Would be Nice to Have:
Prior experience in software engineering for AR/VR projects.
Prior experience with large data Multi-INT analytics, ML, and automated predictive analytics.
Advanced skills as a software developer in open source and proprietary software languages (C++, Python, Java)
Prior experience using Databricks to perform data transformations or modeling, analyzing algorithms, writing scripts, building predictive analytics, using automation, applying machine learning (ML), and use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help leaders make informed decisions.
Prior expertise in predictive modeling and the ability to deliver business-oriented communications for technical and non-technical audiences and Creating data visualizations and reports to communicate findings effectively.
Secret-level security clearance. (US Citizenship is required in order to obtain a security clearance from the DoD.)
What We Can Offer You:
We’ve been named a Best Place to Work by the Washington Post.
Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives.
We offer competitive benefits and learning and development opportunities.
We are mission-oriented and ever vigilant in aligning our solutions with the nation’s highest priorities.
For over 60 years, the principles of CACI’s unique, character-based culture have been the driving force behind our success.
Company Overview: At CACI, you will have the opportunity to make an immediate impact by providing information solutions and services in support of national security missions and government transformation for Intelligence, Defense, and Federal Civilian customers. CACI is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other protected characteristic.