User Growth Algorithm Engineer (Local Services) - TikTok Data

Description

The TikTok-Data-Local Services International Local Life Algorithm Team is responsible for the algorithms of TikTok's global local life, including incentive growth, user growth recommendation, transaction scale recommendation, content understanding, AIGC content generation, generative recommendation and other directions. The optimized scenarios cover the TikTok recommendation page and the local page. Here you can cooperate with the top algorithm engineers in the industry, give full play to your advantages in deep learning, recommendation algorithms, large models and AIGC, and continuously change and improve the TikTok user experience, and transaction volume. The team members are located in Beijing, Shanghai, Singapore and the United States. They mainly come from top companies and well-known universities in the industry, and the team continues to introduce outstanding talents.

Job Description
1. Develop user growth algorithms for TikTok Local Services (e.g., dining, accommodation), focusing on core objectives such as user acquisition, activation, and GMV growth, and building systematic growth strategies and algorithmic frameworks.
2. Apply methods including Causal Inference, Uplift Modeling, Reinforcement Learning, and Large Language Models (LLMs), integrating multi-source data to scientifically evaluate and optimize growth strategies and ROI.
3. Gain deep insights into local services business characteristics and user behavior, identify algorithmic opportunities across scenarios such as dining and accommodation, and continuously improve business conversion efficiency.

Requirements

Minimum Qualifications：
1. Master’s degree or above in Computer Science, Statistics, Mathematics, Operations Research, or related fields.
2. Experience in areas such as causal inference, uplift modeling, reinforcement learning, or operations research optimization is preferred.
3. Solid understanding of machine learning and deep learning fundamentals, with proficiency in mainstream frameworks such as TensorFlow or PyTorch.
4. Strong programming skills and solid foundations in data structures and algorithms; proficient in at least one of Python, C++, or Java.
5. Excellent problem decomposition and problem-solving skills, with strong cross-functional communication abilities and the capability to translate algorithmic solutions into business impact.