Senior Data Scientist - Machine Learning Data Operations - TurbineOne : Job Details

Senior Data Scientist - Machine Learning Data Operations

ABOUT THE JOB

Company: TurbineOne — TurbineOne is the frontline perception company. We deliver decision advantage, better situational awareness, and stronger force protection. The company is a small, fast-moving startup backed by defense tech venture capitalists. TurbineOne is deployed by every branch of the Department of Defense to solve critical missions.

• Reporting to the Machine Learning team lead
• Geographically flexible for home-office

Responsibilities

• Ingesting, organizing, and maintaining large-scale training datasets from open-source resources and contract-specific artifacts
• Creating and managing data cataloging systems to ensure datasets are findable, accessible, and ready for ML training pipelines
• Designing and implementing data labeling workflows, including managing external labeling vendors and quality assurance processes
• Building and maintaining YOLO-style manifests and annotation formats for custom computer vision datasets
• Performing data cleaning, validation, and augmentation to ensure high-quality training data
• Conducting exploratory data analysis and generating insights about dataset characteristics, biases, and coverage gaps
• Supporting the ML research team with statistical analysis, experiment design, and model evaluation
• Developing data pipelines and automation tools for continuous data ingestion and processing
• Collaborating with ML engineers to optimize data loading and preprocessing for training efficiency

On a Typical Day You Would

• Process incoming datasets from various sources, performing quality checks and organizing them into our data management system
• Create or review annotation schemas and coordinate with labeling teams to ensure consistent, high-quality labels
• Write Python scripts to clean, transform, and validate datasets for specific ML training requirements
• Analyze dataset statistics and create visualizations to identify potential issues or opportunities for improvement
• Collaborate with the ML research lead to design experiments and evaluate model performance across different data splits
• Document dataset characteristics, versioning, and lineage to maintain reproducibility and compliance

Desired Experience

• High standard of ethics, grit, integrity and moral character
• 5+ years of experience in data science, analytics, or related field with focus on ML data preparation
• Strong foundation in probability, statistics, and experimental design
• Bachelor's degree in Statistics, Mathematics, Computer Science, or related quantitative field (Master's preferred)
• Proficiency with Python data stack: Pandas, NumPy, Jupyter Notebooks, and data visualization libraries
• Experience with ML frameworks (PyTorch, Scikit-learn) and familiarity with training workflows
• Hands-on experience with computer vision datasets and annotation formats (COCO, YOLO, Pascal VOC)
• Experience managing data labeling projects and working with annotation tools (Label Studio, CVAT, or similar)
• Familiarity with open-source ML models and experience applying them to real-world problems
• Strong SQL skills and experience with data warehousing concepts
• Experience with version control (Git) and collaborative development practices
• Excellent communication skills for coordinating with technical and non-technical stakeholders
• Meticulous attention to detail and strong organizational skills for managing complex datasets
• Willingness to embrace the Startup Culture of moving fast, being insatiably curious, celebrating often, embracing uncertainty, and having a personal desire to improve other peoples' lives

Nice to Have

• Experience with defense or security-related datasets
• Knowledge of edge computing constraints and data optimization techniques
• Experience with distributed data processing frameworks (Spark, Dask)
• Familiarity with MLOps practices and tools
• Background in specific domains relevant to perception systems (satellite imagery, sensor fusion, etc.)

Startup Culture Expectations

• We\'re a small, fully remote team and everything is our responsibility
• Our team thrives on autonomy, trust and solid communication
• Everyone on the Team needs to be very comfortable with constant change, moving fast, sharing failures, embracing grit, and building things themselves

Eligibility

• Must be eligible to obtain a clearance with the U.S. government

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Engineering and Information Technology

Industries

• Defense & Space

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