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Company Overview
This company is a global platform for short-form mobile video. Their mission is to inspire creativity and bring joy. With offices around the world, they are dedicated to building a community where creators can express themselves and users can discover engaging and authentic content. Their e-commerce initiatives are rapidly growing, creating exciting opportunities to leverage data and machine learning to enhance user and seller experiences.
As a Machine Learning Engineer in the e-Commerce Data Compass team, you will:
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.
Disclaimer
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No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
No Client Relationship: This company is not a client of SpringCube unless stated.
To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
No Liability: SpringCube is not liable for inaccuracies.
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