Data Analyst for AI Service and Operations

4 days ago

Sydney, New South Wales, Australia TikTok Full time
About the Team

The AI Data Service and Operations team is responsible for providing safety and non-safety data annotation services and search operation services for all of TikTok's international products. As a Business Insights Analyst for AI Data Service and Operations, you'll analyze market trends, conduct competitor analysis, and provide actionable insights to drive business decisions. You'll require a strong background in market research and data analysis, with a keen interest in artificial intelligence and machine learning.

Key Responsibilities:

  1. Conduct comprehensive market research to identify industry trends, competitive landscape, risks, and opportunities in the AI data annotation sector.
  2. Keep close to business operations to understand priorities, challenges, and provide relevant research findings to support the business.
  3. Independently lead a research scope from start to end, including scoping requirements, fieldwork, report writing, and presentation of findings.
  4. Use both quantitative and qualitative analysis methods to deliver well-rounded research findings.
  5. Monitor and generate regular trend reports to evaluate the impact of the latest developments in the AI industry, regulatory changes, and other external factors on our operations.
  6. Stay up-to-date with the latest developments in AI and machine learning, particularly as they relate to data annotation and labeling.
  7. Participate in industry conferences, webinars, and other events to network with key stakeholders and gather relevant insights.

Requirements:

  1. Bachelor's degree in Business, Economics, Data Science, or a related field.
  2. Proven track record in conducting industry research and analysis preferably within the technology or AI sectors.
  3. Strong analytical skills with the ability to interpret complex datasets and translate them into actionable insights.
  4. Excellent written and verbal communication skills, with the ability to present findings clearly and concisely to a variety of audiences.
  5. Proficiency in market research tools and techniques, including data collection, statistical analysis, and trend forecasting.
  6. Familiarity with AI and machine learning concepts, particularly in the context of data annotation and labeling.
  7. Ability to work in a high-tempo environment, adapt, respond to day-to-day challenges of the role, and maintain resilience and commitment to self-care.

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