Software Data Scientist-Journeyman
📋 About the job
Job Summary
The Software Data Scientist-Journeyman supports Battlespace Modeling & Simulation by developing and validating data-driven solutions for modeling, simulation, testing, and analysis environments. The role involves collaborating with cross-functional teams to verify system performance, analyze complex datasets, build and maintain data pipelines, and generate actionable insights. Responsibilities include data cleaning, visualization, statistical analysis, automation using Python, SQL querying, and supporting verification and validation activities. The position also requires ensuring software quality through testing, documentation, and collaboration with technical teams while presenting findings to both technical and non-technical stakeholders.
Education, Experience & Qualifications
- High School Diploma or equivalent.
- 5 years of relevant professional experience.
- 5 years of experience with Python (3.11+) for scripting, automation, and data processing.
- 5 years of experience with Pandas and NumPy.
- 3 years of experience with SQL (PostgreSQL).
- Experience designing, building, and validating data pipelines.
- Strong understanding of statistics, hypothesis testing, exploratory data analysis (EDA), and data validation.
- Experience with Git version control and collaborative development.
- Ability to obtain and maintain required DoD security clearance.
- Bachelor's degree in Computer Science, Data Analytics, Engineering, Mathematics, Cyber Security, Information Technology, or related field (preferred).
- Experience with data visualization tools (Matplotlib), workflow orchestration tools (Luigi, Airflow, Prefect, Dagster), Docker, or Ansible (preferred).
Knowledge & Skills
- Python programming and automation.
- Data analysis, cleansing, and feature engineering.
- SQL database querying and optimization.
- Statistical analysis and data science methodologies.
- Data visualization and reporting.
- Data pipeline development and validation.
- Software testing and code quality practices.
- Version control using Git.
- Problem-solving and analytical thinking.
- Technical documentation and communication.
- Ability to work independently and within cross-functional teams.