Data / Operations Research Analyst

P17 Solutions LLC•Oklahoma City, OK

1d•$72,000 - $145,000•Onsite

About The Position

P17 Solutions is seeking a Data Analyst / Operations Research Analyst to join our team supporting the Federal Aviation Administration (FAA) Technical Operations Resiliency, Innovation, Sustainment, and Engineering (RISE) Program. This is a full-time position preferred on-site in Oklahoma City, OK, with remote and alternative location arrangements considered. The Data Analyst / Operations Research Analyst will bring mid- to senior-level expertise in data extraction, statistical analysis, and executive-level data visualization to support data-driven decision-making across the RISE program. This role focuses on transforming complex backend operational data into clear, actionable business intelligence through the design and maintenance of intuitive dashboards, quick-turn analytics, and narrative reporting delivered to FAA leadership and program stakeholders. The ideal candidate brings demonstrated experience working with Technical Operations (Tech Ops) Data, National Airspace System (NAS) and FAA organizational structure, and equipment logging data with a combined proficiency in SQL, Python or R, and visualization platforms such as Tableau or Databricks is strongly preferred.

Requirements

Proficiency in SQL for data extraction and preparation, including complex joins and aggregations.
Experience with advanced analytical functions like CTEs and Window Functions.
Experience preparing and cleaning data.
Proficiency in Python or R for statistical analysis and quick-turn analytics.
Experience with exploratory data analysis (EDA), hypothesis testing, and probability modeling.
Skilled in data manipulation for cleaning, filtering, and grouping large datasets.
Experience building custom charts using Python visualization libraries (e.g., Matplotlib, Seaborn).
Competency in designing interactive dashboards using platforms like Tableau or Databricks.
Ability to connect custom SQL scripts to visualization platforms.
Experience with data blending and using Level of Detail (LOD) expressions in Tableau.
Mastery of visual grammar to select appropriate charts for data properties.
Ability to build narratives from statistical summaries.
Strong oral and written communication skills.
Bachelor's degree (or higher) in Mathematics, Statistics, Computer Science, Data Science, or a directly related field.
5+ years of relevant experience OR a combination of education and experience (30+ semester hours in relevant disciplines plus 10+ years of experience).
US citizen or current green card holder with the last 3 consecutive years as a resident of the US.
Ability to obtain and maintain a Government clearance.

Nice To Haves

Demonstrated experience working with Technical Operations (Tech Ops) Data.
Experience with National Airspace System (NAS) and FAA organizational structure.
Experience with equipment logging data.
Proficiency in visualization platforms such as Tableau or Databricks.
Direct experience working with FAA systems, including RMLS, FSEP, NASPAS, IFS, PURE, and Delphi.
Foundational understanding of the NAS, including general NAS equipment and service purposes, FAA organizational structure, and equipment logging fields and their operational meanings.

Responsibilities

Extract and reshape data from databases using inner, left, right, and full outer joins, including proper handling of NULL values.
Utilize Common Table Expressions (CTEs) and Window Functions to calculate advanced metrics (e.g., running totals, moving averages).
Prepare and clean tables through date alignment and string manipulations prior to visualization or modeling.
Write programmatic scripts to conduct quick EDA, hypothesis testing, and probability modeling to uncover hidden insights.
Rapidly clean, filter, and group massive datasets to bridge the gap between initial exploration and predictive science.
Build custom chart layers, scales, and color hierarchies within Python visualization libraries (e.g., Matplotlib, Seaborn).
Structure actions, parameters, and drill-down filters to build automated, easily digestible executive dashboards.
Connect custom SQL scripts directly to Tableau, blend data sources, and utilize Level of Detail (LOD) expressions to maintain stable comparative calculations during user interaction.
Select the mathematically correct chart for specific data properties (e.g., scatter plots for correlation, time series for historical trends).
Distill dense statistical summaries into cohesive narratives focused directly on KPIs and actionable business insights.
Effectively convey technical findings to non-technical leadership and varied audiences.