Remote Data Scientist — AI Model Evaluator & Quality Lead

Island Jobs; Philippines; Teletrabalho; PHP 1 736 000 - 4 340 000; Tempo parcial

Resumo da oferta

TELUS Digital is seeking a data scientist to join its AI Community as an independent contractor. You will perform diagnostic testing on model performance, uncover biases, and provide statistical evidence to push AI capabilities.

You will architect evaluation frameworks, wrangle data for large language models, detect failures, visualize trends, and develop automated scripts to monitor data quality across global projects.

Qualificações

• Minimum of a Bachelor’s Degree in Data Science, Mathematics, Statistics, Physics, or a related technical field.
• English Proficiency: Minimum B1 (Intermediate) level English to communicate data trends.
• Language: Native-level fluency in at least one language.
• Technical Skills: Basic proficiency in data manipulation (e.g., Python, SQL, or Excel).

Responsabilidades

• Architect and execute evaluation frameworks to measure model accuracy, helpfulness, and safety across massive datasets.
• Perform advanced data-wrangling to transform raw text into optimized training sets for Large Language Models (LLMs).
• Detect and visualize complex trends in model failures, providing actionable insights that guide the next phase of AI training.
• Develop automated scripts to monitor the consistency of human-annotated data, ensuring the quality standards of TELUS Digital are met.

Conhecimentos

English proficiency B1

Native language fluency

Data manipulation basics

Formação académica

Bachelor's degree in Data Science, Mathematics, Statistics, Physics, or related field

Ferramentas

Python

SQL

Excel

Descrição da oferta de emprego

TELUS Digital is seeking a data scientist to join its AI Community as an independent contractor. You will perform diagnostic testing on model performance, uncover biases, and provide statistical evidence to push AI capabilities.

You will architect evaluation frameworks, wrangle data for large language models, detect failures, visualize trends, and develop automated scripts to monitor data quality across global projects.