TurbineOne

Senior Data Scientist, Machine Learning Data Operations

TurbineOne

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Job Level

Senior

Tech Stack

NumpyPandasPythonPyTorchScikit-LearnSparkSQL

About the role

  • 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
  • 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

Requirements

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