Data Scientist

CACI International•Norfolk, VA

18d•$114,600 - $252,100•Onsite

About The Position

CACI has an immediate opening for a Data Scientist supporting the United States Fleet Forces Command (USFFC) N41 under the Naval Forces Logistics (NFL) II contract on site at our Hampton Roads location. In this role, you will bridge the gap between complex military logistics operations and advanced analytics. You will formulate and lead guided, multifaceted analytic studies against massive volumes of structured and unstructured data. Because predictive modeling relies on a flawless data foundation, a major component of this role involves hands-on data engineering, building the pipelines, cleaning the data, and organizing the datasets required to drive advanced analytics. As a Lead, you will manage the day-to-day execution of data projects, provide technical oversight, and ensure the integrity, accessibility, and readiness of data for real-time operational decision making.

Requirements

Current and active Secret Clearance
Bachelor’s degree Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or a relevant technical field.
10 or more years of experience in a software development, logistics, data science or related role.
Of which must include at least five (5) years of professional experience in data science.
Proven experience designing scalable data pipelines using Medallion Architecture (Bronze, Silver, Gold layers).
Advanced SQL for complex transformations/query optimization, alongside Python or PySpark for data wrangling and automation.
Expertise in data modeling (star/snowflake schemas, Kimball, Inmon), ERDs, semantic modeling, and modern tools like dbt.
Hands-on experience with Databricks, Apache Spark, Snowflake, Redshift, BigQuery, AWS, Azure, or GCP data engineering services.
Direct experience utilizing the War Data Platform (ADVANA), Maven/Palantir platforms, and Qlik Sense for data integration.
Familiarity with legacy data lakes (Hadoop, Delta Lake), real-time streaming tools (Apache Kafka, Flink), and modern CI/CD pipelines (Infrastructure as Code).
Proficiency in at least one programming language (e.g., Python, R, Java, C++).
Demonstrated experience leading a team

Nice To Haves

Masters Degree preferred (In lieu of the Master’s degree, ten (10) years of industry experience in data science may be substituted. (Note: Education equivalency experience is in addition to the minimum 5 years of experience, totaling 15 years of experience without a Master's degree).
Minimum of eight (8) years of hands-on experience in a combination of Navy logistics and Navy logistics Automated Information Systems (AIS) management.
Software Development skills

Responsibilities

Formulate and lead guided, multifaceted analytic studies using exploratory mathematics, statistical techniques, and the scientific method.
Apply advanced methods including machine learning, statistical modeling, and artificial intelligence to measure and improve logistical outcomes.
Build predictive models and machine-learning algorithms, combining them through ensemble modeling to discover hidden trends and patterns.
Experiment against data points to extract actionable insights and provide previously undiscovered solutions to command data challenges.
Clean, massage, and organize highly complex, unstructured, and structured datasets using modern programming languages (e.g., Python, R, Java, C++).
Align and optimize: Work closely with all stakeholders to align your data pipelines and deliverables with the established strategy for the long-term data platform architecture.
Design and streamline scalable ETL/ELT data pipelines, SQL queries, and models to optimize overall system performance.
Build interactive dashboards and reports utilizing enterprise visualization tools to deliver clear insights to senior leadership.
Act as lead and oversee data governance.
Present information and deliver clear insights to senior leadership using advanced data visualization techniques and enterprise dashboard.
Lead data analytics efforts by delegating tasks, managing project workflows, and serving as the primary liaison to external departments.
Develop methodology and processes for the prioritization and scheduling of team projects.
Analyze problems to determine root causes and implement data quality, validation, and governance protocols.