DoD/IC Data Scientist: Python, ML & Visualization

Applied Research Laboratory at the Penn State University; Honolulu (HI); On-site; USD 111,000 - 182,000; Full time

Job summary

Applied Research Laboratory at the Penn State University seeks a Data Scientist to join the Information Advantage Office in Honolulu, HI. You will lead analytics using Python, data science libraries, and visualization tools to support mission-critical objectives in DoD/IC data environments.

The role may be filled as Senior Data Scientist, with responsibilities including data pipelines, dashboards, and mentoring colleagues while ensuring rigorous statistical practices and reproducibility.

Qualifications

• Master's degree with 6+ years of relevant experience or equivalent.
• Strong Python and data science library experience (pandas, NumPy, scikit-learn).
• Proficiency in data visualization and BI tools for senior leadership.
• Experience with SQL and NoSQL databases in production.

Responsibilities

• Design and conduct exploratory data analysis and hypothesis testing.
• Develop interactive dashboards and visualizations for decision-makers.
• Build Python-based data pipelines using common libraries.
• Integrate diverse data formats across relational and NoSQL databases.
• Apply advanced data mining and ML techniques to large datasets.
• Mentor junior data scientists and analysts; promote reproducibility.

Skills

Python

Data science libraries

Data visualization

SQL

NoSQL databases

Education

Master's degree

Tools

Power BI

Tableau

Grafana

PostgreSQL

MongoDB

Job description

Applied Research Laboratory at the Penn State University seeks a Data Scientist to join the Information Advantage Office in Honolulu, HI. You will lead analytics using Python, data science libraries, and visualization tools to support mission-critical objectives in DoD/IC data environments.

The role may be filled as Senior Data Scientist, with responsibilities including data pipelines, dashboards, and mentoring colleagues while ensuring rigorous statistical practices and reproducibility.