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Data Scientist (Local Services) - TikTok

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新加坡 · Singapore · 经验要求见详情
ProductData analysisRegularA53056新加坡国际招聘TikTok

关于这个机会

About the Team TikTok’s data scientist team is a critical component of the platform’s success, responsible for leveraging data to enhance user experience, optimize content delivery, and drive business decisions. As a leading social media app known for its short-form video content, TikTok relies heavily on data science to stay ahead in a vibrant market. Job Description 1. Build and improve the operational data infrastructure for TikTok local services. This includes managing both online and offline activities, video-merchant matching processes, transaction processes, search/recommendation modules, traffic monitoring, and supply monitoring. Ensure data accuracy and alignment with business scenarios. 2. Develop a deep understanding of the impact of operational activities on transaction conversion rates and scientifically calculate the contribution of each activity to transaction improvements across various industries. 3. Regularly monitor key metrics, clearly identify reasons for metric fluctuations, and provide optimization and improvement suggestions. 4. Enhance communication with the business team, regularly produce analysis reports, and proactively help the business identify potential growth opportunities.

任职要求

Minimum Qualifications 1. Bachelor’s degree or higher, with over 3 years of work experience 2. Background in data-related fields such as statistics, computer science, or quantitative analysis. Experience in model development (causal inference, data mining, etc.) 3. Strong curiosity, the ability to proactively understand business needs, quickly grasp business logic, and translate it into data-driven problems. Preferred Qualification 1. Excellent communication and coordination skills, with the ability to collaborate effectively across departments. 2. Strong sense of ownership, responsibility, and teamwork.

官方来源与核验

字节跳动官方招聘 · 职位编号 7428856740463315251

最近核验:2026-09-16T12:31:41.068845+00:00

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