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Machine Learning Engineer (Recommendation) - TikTok e-Commerce Data Compass
Machine Learning Engineer (Recommendation) - TikTok e-Commerce Data Compass-March 2024
Singapore
Mar 16, 2025
ABOUT TIKTOK
As the leading destination for short-form mobile video, TikTok’s mission is to inspire creativity and bring joy.
5,001 - 10,000 employees
Social Media, Technology
VIEW COMPANY PROFILE >>
About Machine Learning Engineer (Recommendation) - TikTok e-Commerce Data Compass

  Responsibilities

  TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul and Tokyo.

  Why Join Us

  Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.

  Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.

  To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.

  At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.

  Join us.

  About the team

  The e-commerce compass team aims to serve merchants and creators on the e-commerce platform to improve the operating efficiency of merchants and creators. The main work of this team is to improve the efficiency of merchandise strategy, user operation, marketing and other directions through algorithm strategy.

  Responsibilities

  - Improve the working efficiency of e-commerce merchants, influencers, and account managers to boost the growth of sellers' products, customers, and revenue.

  - Participate in the optimization of sellers' operations, such as marketing insights, assortment planning, customer relationship management (CRM), anomaly detection, and diagnostic attribution.

  - Participate in the optimization of merchandise operations, such as seasonal and trend analysis, supply and demand analysis, new product and product growth analysis, and improving the alignment of products and associated traffic.

  - Participate in the optimization of the marketing strategies and Return on Investment (ROI) of sellers and influencers in TikTok e-commerce live streaming, short video, and ShopTab.

  - Analyze and conduct feature engineering for massive data such as customer profiling, e-commerce transactions, relationships between products, business opportunities, and deploy the model pipeline.

  - Use techniques such as representation learning, graph modelling, causal inference, and time series forecasting to assist merchants and influencers in problem-solving and discovering growth opportunities.

  Qualifications

  - Bachelor's degree with a strong preference for fields of study in computer science, statistics, and data mining.

  - Experienced with feature engineering from massive raw data, such as customer/shop/influencer profiling and e-commerce transactions.

  - Solid understanding and hands-on experience with data structures algorithms, machine learning models such as boosting trees, logistic regression, and clustering.

  - Proficient coding skills using Python, Spark, Tensorflow/PyTorch, and other deep learning tools.

  - Experience in search and recommendation systems, with an emphasis on AIGC field is a plus.

  - A strong desire to learn and discover new things, result-oriented, customer-oriented, team player, and self-driven.

  - At least 3 years of relevant experience.

  TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

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