Data Analyst

Job Description: Data Analyst AI Systems

About the Role:

We are seeking a Data Analyst to join our AI team, focused on data cleaning, dataset curation, annotation quality control, and model performance analysis for AI systems deployed in real-world environments.

Key Responsibilities

Data Cleaning & Dataset Curation

• Clean, validate, and preprocess customer-generated radar, image, and video datasets
• Identify and resolve corrupted, duplicate, mislabeled, or low-quality data samples
• Curate datasets for training, validation, and testing to support model development
• Maintain dataset versions, metadata, lineage, and documentation
• Ensure data quality standards are consistently met across datasets

Annotation & Labeling Quality Control

• Manage and coordinate external annotation resources (e.g., Upwork contractors or vendors)
• Review labeled images and videos to ensure accuracy, consistency, and guideline adherence
• Provide clear feedback, examples, and labeling instructions to annotators
• Track and report on annotation quality, turnaround time, and recurring issues
• Collaborate with the AI team to design, implement, and maintain a quality control (QC) pipeline for data labeling

Model Performance & Data Analysis Support

• Analyze annotated datasets to identify patterns, errors, and data gaps
• Support AI engineers with model evaluation and error analysis
• Monitor basic model performance metrics such as accuracy, precision, recall, and confusion matrices
• Help identify data-driven improvements to model performance in production environments.

Required Qualifications

• 25 years of experience as a Data Analyst, Applied Data Scientist, or similar role
• Strong proficiency in Python , including Pandas, NumPy, and scripting
• Proven experience cleaning and validating messy, real-world datasets
• Comfort working with unstructured data , such as radar signals, images, videos, or logs
• Working knowledge of SQL ; experience with Snowflake preferred
• Understanding of basic ML model evaluation metrics
• Exceptional attention to detail and strong focus on data quality.