Data Scientist - Active Secret Clearance Required

MTSI is seeking a Data Scientist to support the USAF Test Pilot School at Edwards AFB, CA.

This position can be hybrid. It will require the ability and willingness to travel to Edwards AFB, CA up to 40%.

The Data Scientist serves as the lead Data Analyst for Doolittle Labs, providing technical leadership across AI/autonomy T&E, data analysis, and standing up the lab’s data-driven test infrastructure. The Data Scientist works under the technical direction of the Director of Data and Analytics and coordinates externally with AFTC Multi-Domain Test Force (MDTF), the AFTC Data Working Group, TRMC, AFRL, and OEM technical partners, among others.

• Establish a “data-driven test” infrastructure and process for Doolittle Labs, aligned with the AFTC Multi-Domain Test Force (MDTF) and AFTC Data Working Group and VAULTIS-compliant for integration into the DAF Data Mesh Environment (DME).
• Support all flight-test activities executed by Doolittle Labs, including modeling and simulation (M&S), test-data planning, and data acquisition requirements definition.
• Support flight-test data analysis post-event, including data received from OEM partners and translation of OEM outputs into Doolittle Labs analysis products.
• Apply data-analysis tools to quantify AI-agent performance early—in simulation, HITL/SITL, and pre-flight environments; before flight test on the X-62A VISTA.
• Provide and disseminate flight-test results to Doolittle Labs leadership, sponsors, PAE/PM reach-back customers, and, where and when authorized and cleared, the broader T&E community.
• Ensure that task related products are consistent in format and content with overall project deliverables - Routinely engage with Govt technical representative + tech leads for our teammates and subcontractors
• Acts as a resource/mentor for colleagues with less experience
• Works independently, with guidance in only the most complex situations

• Deep knowledge of statistical methods, machine learning, and modern data-science techniques; such as regression, classification, clustering, deep learning, time-series analysis, and uncertainty quantification; as applied to research and development, engineering, and flight test data.
• Knowledge of flight test methodologies, including test-plan development, test-point matrix construction, telemetry acquisition, post-flight reconstruction, and safety-of-flight considerations.
• Familiarity with AI/autonomy T&E challenges, including verification and validation (V&V) of nondeterministic systems, human-agent trust calibration, demonstration of operational AI systems, and multi-agent scenarios. Familiarity with recent X-62 flight test campaigns (e.g., HAVE HEAT, DARPA ACE, HAVE HOLIDAYS) is a plus.
• Familiarity with the DAF Data Strategy (VAULTIS, DME, Domain Principals), the DoD Cyber Workforce Framework (DCWF) data work roles and KSATs, and applicable AFTC and AFMC data governance.
• Knowledge of applicable federal and DoD policies governing controlled unclassified information (CUI), classified test data, intellectual property, and OEM data-rights posture (IAW DoW IP Guide).
• Proficiency with Python (e.g., pandas, Num Py, scikit-learn, PyTorch, Tensor Flow) and at least one additional statistical/scientific computing environment (R, MATLAB, Julia).
• Experience with modern data engineering (SQL, cloud-native data warehouses, Parquet/Arrow, ETL pipelines) sufficient to design and build the Doolittle Labs data spine.
• Experience with modeling-and-simulation environments used in flight test (MATLAB/Simulink, JSBSim, HITL/SITL benches) and their integration with data-analysis workflows.
• Experience with visualization and results communication (Tableau, Power BI, matplotlib,…