Staff Data Scientist
Quartermaster
full-time
Posted on:
Location Type: Hybrid
Location: Arlington • Virginia • United States
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Job Level
Tech Stack
About the role
- Analyze large volumes of structured and unstructured data from field deployments to uncover trends, anomalies, and actionable insights for customers.
- Develop scalable analytics pipelines to support customer-facing dashboards, reports, and intelligence products.
- Collaborate with product and customer success teams to frame high-value business and operational questions and translate them into data science workflows.
- Identify performance gaps, failure modes, and drift in edge-deployed models by analyzing historical outputs, sensor metadata, and ground-truth comparisons.
- Partner with the modeling team to design feedback mechanisms for continuous learning, dataset enrichment, and model retraining.
- Build tools and internal services for data visualization, metric tracking, and experimentation across field data.
- Contribute to the design and refinement of metrics for evaluating perception, detection, and fusion performance across time and space.
- Ensure data quality and integrity across the pipeline, including logging validation, schema enforcement, and anomaly detection.
- Stay current with best practices in large-scale data analytics, monitoring, and applied ML, and advocate for their integration into team workflows.
Requirements
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field
- 3–5 years of experience in applied data science, with a track record of translating raw data into production insights or tools.
- Proficiency in Python and common data science libraries (e.g., pandas, numpy, scikit-learn, matplotlib/seaborn, SQL).
- Experience working with time-series, geospatial, or multi-sensor data in production environments.
- Strong analytical thinking and statistical modeling skills, including clustering, regression, and anomaly detection
- Familiarity with ML operations concepts like dataset versioning, data labeling workflows, and model monitoring
- Excellent communication skills for presenting complex insights to both technical and non-technical stakeholders
- Bonus: experience supporting or analyzing ML systems at the edge, or in environments like maritime, automotive, or aerospace domains.
Benefits
- Flexible working hours with occasional deadlines requiring high availability.
- Opportunity to work on innovative projects with a global impact.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data analysisdata visualizationPythonpandasnumpyscikit-learnmatplotlibSQLstatistical modelinganomaly detection
Soft Skills
analytical thinkingcommunication skillscollaborationproblem-solvingattention to detailadaptabilitycritical thinkingcreativitytime managementteamwork
Certifications
Bachelor’s degree in Data ScienceMaster’s degree in Data ScienceBachelor’s degree in StatisticsMaster’s degree in StatisticsBachelor’s degree in Computer ScienceMaster’s degree in Computer Science