Data Acquisition Analyst ( Japanese, French) - R01572719

Brillio•Dallas, TX
•$30 - $35•Hybrid

About The Position

At Brillio, the AI Training Data Acquisition Analyst will collect, process, and analyze data from various sources, working with Data Scientists and Engineers to support data-driven decision-making and product development. The role supports the development of AI technologies and customer expectations. The analyst labels collected data to train AI models for in-field scam and deepfake detection; cleans, validates, and transforms data using analytical tools and programming languages such as Python and Node; and extracts and integrates data from sources including databases, APIs, and web scraping. The analyst also communicates findings and recommendations to stakeholders using clear language and visuals, collaborates on data modeling, machine learning, and experimentation, and keeps up with developments in data science. The position is based in Frisco two days per week, with the remaining work remote. Japanese and French language skills are the top priorities; German and Spanish are less important.

Requirements

  • Interest in data science and willingness to learn and apply new skills and tools.
  • Skills in organizing data and attention to detail.
  • Ability to work independently and as part of a team.
  • Excellent communication and presentation skills.
  • Japanese and French language skills are top priorities; German and Spanish are less important.

Nice To Haves

  • Experience with Python or a similar programming language and data manipulation.

Responsibilities

  • Apply labels to collected data for training AI models used in in-field scam and deepfake detection.
  • Clean, validate, and transform data using analytical tools and programming languages such as Python and Node.
  • Extract and integrate data from databases, APIs, web scraping, and other sources.
  • Communicate findings and recommendations to stakeholders using clear language and visuals.
  • Collaborate with data scientists and engineers to support data modeling, machine learning, and experimentation.
  • Keep up to date with trends and developments in data science and related fields.
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