Data Scientist - Mid - #918

Allen Integrated SolutionsDayton, OH
Onsite

About The Position

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.

Requirements

  • 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.
  • 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).
  • Active TS/SCI security clearance for 100% on-site support at Wright-Patterson AFB.
  • Familiarity with fundamental DoD cybersecurity protocols and information management profiles.

Nice To Haves

  • NASIC experience highly desired, not mandatory.

Responsibilities

  • 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.
  • Develops and updates automated program dashboards and data visualization portals using toolsets approved for the NASIC Unified Cloud (NUC).
  • Assists in applying metadata governance standards and data structures to incoming datasets, verifying that raw data frames align with enterprise data ontology frameworks.
  • 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.
  • Collaborates with senior data scientists to troubleshoot minor data ingestion errors, fix dashboard bugs, and execute scheduled database maintenance scripts.
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