Data QA (Marketplace - Data Science)

Singapore

Applications have closed

The mission of the Marketplace Data team is to build sustainable and scalable data products to promote the business and mission of Shopee marketplace by analyzing massive item and user related data, producing reliable predictive business insights and data-driven services, maximising the effectiveness of marketing campaigns as well as providing personalised e-commerce experiences based on all-round item profiling and user profiling data and information.

Job Description

  • Collaborated with Data Science team to get high quality data serving for shopee ML product
  • Design the data annotation pipelines and strategies to obtain the high quality data in efficient ways including acquisition of data, annotation QA and data QC etc
  • Prepare the annotation guidelines and materials which requires good understanding of both business and data science techniques at shopee
  • Train the local annotators to understand and annotate data based on different tasks
  • Apply analytical skills on optimizing the annotation and annotator quality, improving the overall annotation pipeline and prioritizing different tasks

 Requirements

  • Fluent in either Bahasa, Thai, Vietnamese or Portuguese language, with the ability to read,  write and comprehend as you will be required to check data annotation in one of these languages
  • Highly organized with strong attention to detail to discover insights of data annotation results
  • Demonstrates attention to detail and critical thinking skills in evaluation of annotation results
  • Familiar with Excel skills

Tags: E-commerce Excel Machine Learning Pipelines

Region: Asia/Pacific
Country: Singapore
Job stats:  12  0  0

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.