The Mid-level Data Scientist applies foundational mathematical programming, statistical analysis, and data validation skills to build, maintain, and test analytical data structures. Working as part of an integrated data science team within the NASIC Technology, Data, and Assessment Division (A9A), this position executes routine data cleaning, maintains production dashboards, and assists in the day-to-day implementation of basic automation routines. The mid-level engineer supports the enterprise software pipeline by preparing high-quality data ingestion models to optimize center-wide analytical throughput.
Core Responsibilities
Data Cleaning & Algorithm Execution: Writes baseline data extraction, transformation, and loading (ETL) scripts. Assists in executing defined IA/AI/ML techniques and running diagnostic checks on active software models.
Dashboard Maintenance & Front-End Design: Develops and updates automated program dashboards and data visualization portals using toolsets approved for the NASIC Unified Cloud (NUC).
Data Flow & Ontology Compliance: Assists in applying metadata governance standards and data structures to incoming datasets, verifying that raw data frames align with enterprise data ontology frameworks.
Sprint & Board Collaboration: Participates fully in daily stand-ups and pure Agile engineering ceremonies on a fixed two-week sprint cadence. Tracks individual task progress using JIRA and documents data pipeline workflows inside Confluence.
Discrepancy Remediation Support: Collaborates with senior data scientists to troubleshoot minor data ingestion errors, fix dashboard bugs, and execute scheduled database maintenance scripts.
Qualifications & Experience
Required:
Education & Experience: Bachelor's degree and 5 years of experience OR a Master's degree and 3 years of experience in Data Science, Computer Science, Information Technology, Statistics, or a related computational field.
Technical Expertise: Experience performing core data manipulation, writing clean SQL or Python code, and handling structured/unstructured databases. Practical, working knowledge of data analytics libraries and code repositories (such as GitLab).
Clearance & Compliance: Active TS/SCI security clearance for 100% on-site support at Wright-Patterson AFB. Familiarity with fundamental DoD cybersecurity protocols and information management profiles.
Desired:
NASIC Experience: NASIC experience highly desired, not mandatory.
Numbers & Facts
Location
Dayton, OH
Skills
Agile Programming Methodologiesunmatched
Algorithmsunmatched
Analysis Skillsunmatched
Artificial Intelligence (AI)unmatched
Atlassian JIRAunmatched
Automationunmatched
Cadenceunmatched
Cloud Computingunmatched
Computer Scienceunmatched
Data Analysisunmatched
Data Cleaningunmatched
Data Managementunmatched
Data Modelingunmatched
Data Qualityunmatched
Data Scienceunmatched
Data Setsunmatched
Data Structuresunmatched
Data Visualizationunmatched
Database Administrationunmatched
Database Extract Transform and Load (ETL)unmatched
Enterprise Applicationsunmatched
Identify Issuesunmatched
Information Technology & Information Systemsunmatched
Internet Securityunmatched
Mathematicsunmatched
Metadataunmatched
On Site Supportunmatched
Ontologyunmatched
Python Programming/Scripting Languageunmatched
Reporting Dashboardsunmatched
SQL (Structured Query Language)unmatched
Scripting (Scripting Languages)unmatched
Security Clearanceunmatched
Sensitive Compartmented Information (SCI)unmatched
Software Administrationunmatched
Software Engineeringunmatched
Standup Meetingsunmatched
Statistical Analysis System (SAS)unmatched
Statistical Programming Languagesunmatched
Statisticsunmatched
Test Dataunmatched
Top Secret Clearanceunmatched
United States Department of Defense (DoD)unmatched
User Interface Designunmatched
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