Data Scientist - Mid - #918

Allen Integrated Solutions, LLC; Dayton (OH); On-site; USD 110,000 - 150,000; Full time

Job summary

The NASIC Technology, Data, and Assessment Division (A9A) seeks a Mid-level Data Scientist to apply statistical analysis, data validation, and ETL skills to build robust data structures and dashboards. This on-site role supports data ingestion and production analytics within an integrated data science team at Wright-Patterson AFB.

You will collaborate in Agile ceremonies, maintain dashboards, and help implement automation while ensuring data governance and ontology compliance for enterprise

Qualifications

• Experience performing core data manipulation and writing clean SQL or Python code.
• Familiarity with data analytics libraries and code repositories (GitLab).
• Active TS/SCI security clearance for on-site support at Wright-Patterson AFB.
• NASIC experience is highly desired but not mandatory.

Responsibilities

• Data Cleaning & Algorithm Execution: Writes baseline ETL scripts and runs IA/AI/ML techniques.
• Dashboard Maintenance & Front-End Design: Maintains automated dashboards and visual portals.
• Data Flow & Ontology Compliance: Applies metadata governance and enterprise ontology standards.
• Sprint & Board Collaboration: Participates in Agile ceremonies and tracks tasks in JIRA.
• Discrepancy Remediation Support: Troubleshoots ingestion issues and performs routine maintenance.

Skills

SQL

Python

Data manipulation

Agile practices

Education

Bachelor’s degree in Data Science / CS / IT / Statistics

Master’s degree in related field

Tools

GitLab

JIRA

Confluence

Job description

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.
• NASIC Experience: NASIC experience highly desired, not mandatory.