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Senior Data Scientist - Machine Learning Data Operations

TurbineOne

Salary not specified
Sep 4, 2025
San Francisco, CA, US
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TurbineOne is seeking a Data Scientist to manage and prepare large-scale training datasets for machine learning models, focusing on computer vision for defense applications. The goal is to automate parts of the military intelligence cycle by providing high-quality, well-organized, and annotated data for ML training.

Requirements

  • 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)
  • Strong SQL skills and experience with data warehousing concepts
  • Experience with version control (Git) and collaborative development practices
  • Strong foundation in probability, statistics, and experimental design

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
  • Developing data pipelines and automation tools for continuous data ingestion and processing

Other

  • High standard of ethics, grit, integrity and moral character
  • 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
  • Must be eligible to obtain a clearance with the U.S. government