Data Science and Data Visualization Subject Matter Expert (SME)

CACI International•Chantilly, VA

16d•$103,800 - $218,100•Onsite

About The Position

CACI is seeking a skilled and motivated Sr. Data Scientist to join our dynamic Data & Analytics team. The ideal candidate will have a strong background in statistics, machine learning, and data mining, with the ability to visualize and communicate complex data clearly and effectively.

Requirements

Active TS/SCI Clearance with CI Polygraph
Minimum of 7 years overall experience and 5+ years of related experience as a Data Scientist, Data Analyst, or similar role
Bachelor’s degree in Data Science, Computer Science, Mathematics, Engineering, or a related field
Proficiency with data visualization tools such as Tableau and Power BI, including data connection, manipulation, and visualization
Hands-on experience with LLMs and generative AI frameworks
Knowledge of statistical analysis methodologies and data visualization practices
Excellent problem‑solving skills and attention to detail
Strong communication and collaboration skills
Ability to work independently and manage multiple projects simultaneously

Nice To Haves

Tableau Certified Professional
Current Security+ or DoD 8570 IAT Level II Certification
Experience with scripting in Tableau (automation, troubleshooting, integration, performance optimization)
Proficiency in Python, R, SQL, and other relevant programming languages
Experience with machine learning, predictive modeling, and data mining
Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes)
Experience with cloud computing platforms and services, particularly in government/classified environments (e.g., AWS GovCloud, Azure Government, C2S)

Responsibilities

Work with cross-functional teams to identify, research, and solve complex analytical problems
Analyze large data sets to extract meaningful insights
Design, build, and maintain machine learning models and algorithms
Collaborate with data engineers to improve data collection and storage processes
Present findings and recommendations to stakeholders in a clear and actionable manner
Support broad Data Management requirements, including: Data Strategy, Modeling, and Documentation Data Feed Identification Infrastructure Management Data Ingestion and Feed Automation Data Transformation Data Catalog and Metadata Management Data Quality Management Data Governance
Evaluate and integrate emerging AI/ML tools and frameworks to enhance analytic capabilities and operational efficiency