Data Scientist

General Dynamics IT; Fort Walton Beach (FL); On-site; USD 110,000 - 160,000; Full time

Job summary

General Dynamics IT seeks a Data Scientist to support government, defense, and intelligence projects by querying, cleaning, and modeling data to generate actionable insights for leadership, with a strong focus on data quality and security.

This role requires TS/SCI clearance and proficiency in Python/R and SQL, along with experience building dashboards and reports using Power BI to enable informed decision making.

Qualifications

• Bachelor's degree in a quantitative discipline with coursework in statistics and programming.
• Minimum of one year of experience applying data science or statistical methods to real-world problems.
• Proficiency in Python or R for data analysis and SQL for querying relational data.
• Working knowledge of applied statistics and supervised/unsupervised machine-learning methods.
• Ability to prepare and clean data for analysis.

Responsibilities

• Query, clean, transform, and prepare data from government sources for analysis.
• Develop, validate, and document predictive and prescriptive models.
• Support NLP use cases to analyze unstructured data with approved tools.
• Develop dashboards and executive reports using Power BI.
• Support analyses measuring ROI and program efficacy.
• Automate recurring analyses and monthly/quarterly reports.
• Document data sources, transformations, and validation procedures.
• Communicate complex concepts to non-technical leadership.
• Collaborate with clinical staff to improve data quality.
• Maintain data quality, security, and privacy controls (IL5, HIPAA).

Skills

Data Analysis

Data Analytics

Data Science

Data Visualization

Statistics

Education

Bachelor's degree in quantitative discipline

Tools

Power BI

Python

R

SQL

Job description

Type of Requisition:

Regular

Clearance Level Must Currently Possess:

Top Secret

Clearance Level Must Be Able to Obtain:

Top Secret/SCI

Public Trust/Other Required:

None

Job Family:

Data Science and Data Engineering

Job Qualifications:

• Skills: Data Analysis, Data Analytics, Data Science, Data Visualization, Statistics
• Certifications: None
• Experience: 0 + years of related experience
• US Citizenship Required: Yes

Job Description:

We are GDIT. The people supporting and securing some of the most complex government, defense, and intelligence projects across the country. We ensure today is safe and tomorrow is smarter. Our work has meaning and impact on the world around us, but also on us, and that's important.

GDIT is your place. You make it your own by embracing autonomy, seizing opportunity, and being rusted to deliver your best every day.

We think. We act. We deliver. There is no challenge we can't turn into opportunity. And our work depends on a Data Scientist joining our team to support customer activities.

HOW DATA SCIENTIST WILL MAKE AN IMPACT:

• Query, clean, transform, and prepare data from the Government-designated Human Performance System of Record (e.g., HPDMS) and other Government-approved sources for analysis, using the curated datasets maintained by the Data Engineer where available.
• Develop, validate, and document predictive and prescriptive models, forecasting methods, clustering, and other advanced statistical techniques to generate actionable forecasts regarding operator readiness, injury risk, program efficacy, and performance optimization, as directed by the Government.
• Support text-heavy use cases using Natural Language Processing (NLP) techniques (e.g., cleaning, entity extraction, classification) to analyze unstructured clinical or survey data and apply Large Language Model (LLM) and agent-style workflows only within Government-approved tools and datasets.
• Develop, deploy, and maintain visual analytics, dashboards, and executive reports using Government-furnished tools (e.g., Power BI, including semantic modeling and DAX), and integrate data products into low-code operational workflows (e.g., Microsoft Power Platform) where directed.
• Support Government-designed analyses and experiments that measure the validity, efficacy, and Return on Investment (ROI) of POTFF interventions, including computation of program-efficacy metrics as directed by the Government.
• Automate recurring analyses and the generation of required monthly and quarterly reports, reducing manual effort and improving accuracy.
• Document data sources, transformations, assumptions, methods, and validation procedures so that analyses are reproducible and can be transferred to other personnel.
• Communicate complex concepts, methods, and results clearly to non-technical command leadership and to clinical and performance staff, in writing and in briefings.
• Collaborate with embedded clinical and performance staff to identify opportunities for capturing data and improving the quality of input into Government systems.
• Maintain rigorous data quality, security, and privacy controls, including DoW Impact Level 5 (IL5), HIPAA, and Privacy Act protocols, in all analytic work.

WHAT YOU'LL NEED TO SUCCEED:

• Education: Bachelor's degree in a quantitative discipline, including but not limited to statistics, biostatistics, mathematics, applied mathematics, data science, operations research, computer science, engineering, physics, economics or econometrics, epidemiology, geospatial science or geoinformatics, or psychology or another behavioral science with a quantitative-methods concentration, with documented coursework or professional application in statistics, programming, and quantitative analysis.
• Minimum of one (1) year of experience applying data science or statistical methods to real-world problems. A Bachelor's degree program that included documented internship, cooperative-education, capstone, thesis, or project work applying data science methods to real-world data satisfies this requirement.
• Demonstrated proficiency in Python or R for data analysis, statistical modeling, and machine learning, and in SQL for querying relational data, demonstrated through professional work experience or degree-program projects.
• Working knowledge of applied statistics and of supervised and unsupervised machine-learning methods.
• Ability to prepare and clean data for analysis,