Ops Research - Data Scientist

CAPE•Washington, DC

19h•Onsite

About The Position

The Cost Assessment and Program Evaluation (CAPE) office is hiring for multiple positions within its Defense Analyst Support Hub (DASH), the data-infrastructure division responsible for operating the shared analytic data and tools ecosystem across CAPE and the broader Department of War analytic enterprise. DASH integrates authoritative defense datasets, manages automated data pipelines, operationalizes simulation models, and develops self-service tools for defense analysts. It also sustains the platform for CAPE's mission analysis environment, runs simulation campaigns, and operates an emulation pipeline under the methods and specifications established by the Strategic Analysis and Analytic Innovation Division (SAID). Depending on role and grade, selectees will work in data and platform engineering, data governance and knowledge management, or on-call analytic tool operation. Duties include building and sustaining automated ETL/ELT pipelines; integrating analytic software into production environments; establishing data schemas, metadata, and validation standards; maintaining authoritative defense baselines and shared analytic repositories; running models and simulation campaigns; overseeing contractor technical deliverables; and cross-training to ensure tools have multiple qualified government operators. GS-14/15 employees may also mentor junior staff and support their professional development. The position is permanent, full-time, and based at the Pentagon in Arlington, Virginia. Applicants must be able to obtain and maintain a Top Secret or Top Secret/SCI clearance; Special Access Program access is required. The position is open to U.S. citizens.

Requirements

A degree in operations research from an accredited college or university, or at least 24 semester hours in a combination of operations research, mathematics, probability, statistics, mathematical logic, science, or subject-matter courses requiring substantial competence in college-level mathematics or statistics; at least 3 of the 24 hours must be in calculus.
At least one year of specialized experience equivalent to the next lower grade level for the grade sought, or the stated doctoral-degree alternative for GS-12.
Ability to obtain and maintain a Top Secret or Top Secret/SCI security clearance; Special Access Program access is required.
GS-12: Experience executing portions of data extraction and loading processes, assisting with pipeline maintenance, running preconfigured analytic models, and documenting workflows under senior staff guidance; alternatively, a Ph.D. or equivalent doctoral degree.
GS-13: Experience writing and optimizing Python, SQL, or R scripts to extract, clean, and transform data; assisting with cloud-native data platforms, databases, or API integrations; executing preconfigured models; documenting tests; troubleshooting schema issues; validating input data; and conducting sensitivity analysis.
GS-14: Experience independently designing, integrating, deploying, and maintaining mathematical models, optimization algorithms, and simulation frameworks; developing analytic baselines and automated ETL/ELT pipelines; integrating advanced algorithms or machine-learning models into production; evaluating contractor deliverables; translating requirements into engineering specifications; and developing dashboards or self-service applications.
GS-15: Experience serving as principal modeling architect or technical authority for analytic or enterprise data infrastructure; directing quantitative data governance and baseline validation; authoring technical roadmaps; leading government technical oversight of contracted engineering support; and developing a multidisciplinary technical workforce.
Knowledge of data engineering, analytic platform architectures, and pipeline construction, scheduling, and optimization.
Knowledge of mathematical modeling and scientific software development or DevOps in an operations research context, including integration or deployment of R, Python, MATLAB, or GAMS models.
Experience with large simulation campaigns and model-serving pipelines for statistical or machine-learning surrogates, including registries, versioning, monitoring, and scheduled refitting.
Knowledge of analytic data management, database schema design, master data management, metadata standards, data integrity, mathematical consistency, and provenance.
Familiarity with operational models, wargaming frameworks, or mathematical program-evaluation tools, and ability to run, debug, and extract results from complex simulation models under deadlines.
Ability to collaborate with platform owners, data stewards, operations research methodologists, and strategic analysts.
Ability to explain technical and analytic concepts in plain language to senior executives and translate analyst needs into technical specifications.

Nice To Haves

Experience with the War Data Platform or other Department of War data systems.

Responsibilities

Design, build, test, and sustain automated data extraction, transformation, and ingestion pipelines for CAPE’s analytic data layer.
Integrate analytic tools and software, including Python, R, MATLAB, and GAMS packages, into a secure shared production platform.
Apply data engineering, containerization, workflow orchestration, and version-control practices to recurring data ingestion and analytic support.
Develop and enforce schemas, taxonomies, metadata definitions, and data validation rules in accordance with SAID analytic-data standards.
Coordinate with Department data owners to curate, reconcile, and maintain governed copies of authoritative defense baselines.
Run program, simulation, and strategic models for CAPE analysts and return results accurately and on time.
Execute simulation campaigns and operate the emulation pipeline, including storing and serving emulators, refitting them as new simulation runs arrive, and launching additional runs as required.
Define technical and operational requirements for contractor deliverables and conduct technical acceptance testing.
Catalog past CAPE analyses and manage shared analytic repositories used by study teams and the Analysis Working Group.
Cross-train in platform engineering and tool operation so that each deployed tool has at least two qualified government operators.
At GS-14/15, mentor junior platform engineers and tool operators and support their professional development.