Systems Engineer

Brandes Associates•Point Mugu, CA

17d•Onsite

About The Position

BAI, a defense contractor, is seeking a Senior Data Analysis Engineer with 10+ years of experience who will be responsible for processing, reducing, analyzing, and evaluating ground laboratory and open-air flight test data for our expanding workforce supporting current and evolving contracts. This role is located at Naval Base Ventura County (NBVC) Naval Air Station (NAS) Point Mugu, CA. BAI offers opportunities for career advancement, excellent benefits, and long-term stability as a growing, employee-focused company.

Requirements

Over 10 years of experience performing the duties described in the functional description.
Excellent technical communication and presentation skills, verbal and written, for briefing Test Directors, Flight Test Engineers, and Program Executive Offices.
Ability to work independently, identifying root causes of system anomalies under dynamic operational conditions.
Demonstrated professional experience analyzing flight test, range, or laboratory experimental data.
Proficiency in developing custom data processing and analysis scripts in Python.
Direct experience working with and correlating TSPI (Time-Space-Position Information) truth data against system data.
Demonstrated capability to decode, parse, and analyze digital avionics bus architectures and telemetry logs.
Experience evaluating system response to threat simulation environments and simulated emitter scenarios.
Advanced skills in Python scripting and data analysis packages for rapid parsing, transformation, and statistical modeling of large, multi-rate time-series datasets.
Knowledge of test range instrumentation, TSPI tracking methods, telemetry acquisition, and ground lab simulation environments.
Ability to identify root causes of system anomalies, evaluate signal-to-noise degradations, and isolate hardware/software failure modes under dynamic operational conditions.
Ability to synthesize complex statistical data into concise, high-impact graphical presentations and brief multi-disciplinary leadership teams to guide high-stakes acquisition decisions.
MS or MA degree in Engineering or a relevant technical discipline such as Aerospace Engineering, Electrical Engineering, Computer Science, Physics, Mathematics, or a related STEM discipline.
An additional 4 years of relevant work experience, with a bachelor's degree, may be substituted for a master's degree.
Applicant must have an active DoD Secret (SSBI-based investigation) Clearance.
The applicants selected will be subject to a security investigation and must meet eligibility requirements for access to classified information.
The applicant must have US citizenship at the time of application.

Nice To Haves

Direct domain experience conducting performance analysis on Radar Warning Receivers (RWR), Electronic Support Measures (ESM), or Electronic Warfare (EW) suites.
Direct experience performing performance analysis on RADAR systems (AESA, Pulse Doppler, synthetic aperture radar).
Familiarity with IRIG 106 Chapter 10/11 data standards and high-density RF threat generation platforms.
Comprehensive knowledge of avionics architectures, radar theory, RF propagation, and signal processing principles to accurately assess sensor detection, tracking, and identification performance.

Responsibilities

Serve as a Senior Data Analysis Engineer responsible for processing, reducing, analyzing, and evaluating ground laboratory and open-air flight test data.
Develops automated Python-based data extraction and analysis pipelines to evaluate complex avionics systems, electronic warfare (EW) suites, and sensor packages.
Analysis directly supports formal verification of system performance requirements and Key Performance Parameters (KPPs), culminating in executive-level presentations and decision-quality technical reports for program managers, test directors, and acquisition authorities.
Ingests, time-synchronizes, and analyzes complex multi-source data collected from ground laboratories, hardware-in-the-loop (HWIL) facilities, installed system test facilities (ISTF), and live-fly open-air range missions.
Evaluates Time-Space-Position Information (TSPI) derived from GPS, ground tracking radar, and optical assets, correlating truth data with onboard avionics recordings and telemetry streams.
Decodes, processes, and analyzes high-throughput avionics digital data buses (e.g., MIL-STD-1553, ARINC 429, Ethernet, Fibre Channel, and IRIG 106 Chapter 10/11 formats).
Evaluates sensor performance, RF threat simulation logs, and emitter identification metrics in both simulated laboratory environments and dynamic flight conditions.
Architects, scripts, tests, and maintains specialized, automated data analysis tools and data reduction pipelines using Python (NumPy, Pandas, SciPy, Matplotlib, and associated libraries).
Builds automated routines for batch-processing raw flight records, identifying data anomalies, performing statistical analysis, and generating standardized verification metrics.
Implements robust software configuration management practices (e.g., Git) and creates reusable modules to accelerate post-flight analysis across multiple test events.
Compares empirical test results against design specifications, system requirements, and interface control documents (ICDs) to identify deviations, anomalies, and performance trends.
Formulates definitive, evidence-based recommendations regarding whether system under test satisfies technical specifications and operational readiness standards.
Authors formal Test & Evaluation (T&E) reports, requirement verification matrices, deficiency reports (DRs), and technical memorandums.
Translates dense telemetry and statistical findings into clear, executive-level presentations, visual dashboards, and briefing slides.
Presents analytical findings to Test Directors, Flight Test Engineers (FTEs), Chief Test Pilots, and Program Executive Offices (PEOs) to support Go/No-Go and milestone acquisition decisions.
Participates in pre-flight test readiness reviews (TRRs) and post-flight debriefs to establish data collection criteria and optimize test point execution.