1 час назад
Staff Data Scientist (SCM)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Staff Data Scientist (SCM) (AI/ML and Operations Research): Developing data-driven solutions for automating supply chain management and supporting large-scale decision-making with an accent on demand forecasting, optimization, and production machine learning. Focus on solving ambiguous operational problems, designing advanced algorithms, and measuring the real-world impact of deployed solutions.
Location: Taipei, Taiwan
Company
develops e-commerce services in Taiwan, including next-day delivery and international delivery from Korea, the U.S., and other markets.
What you will do
- Collaborate with product, engineering, business, and operations teams to translate ambiguous supply chain requirements into practical technology solutions.
- Conduct research, data analysis, experiment design, and metric development for model evaluation.
- Build data-driven solutions for automated decision-making using statistics, machine learning, and operations research.
- Analyze complex data problems with methods including deep learning and communicate findings through reports and presentations.
- Evaluate launched solutions using real-world results and identify opportunities for improvement.
Requirements
- Bachelor’s or master’s degree in a quantitative discipline and 5+ years of relevant industry or academic experience.
- Hands-on knowledge of statistics and machine learning fundamentals, with experience using Python, SQL, and visualization tools such as Tableau or Power BI.
- Ability to independently formulate business problems, manipulate data, design hypotheses and experiments, and perform statistical analysis.
- Strong critical-thinking, problem-solving, written communication, and presentation skills.
Nice to have
- Advanced experience with Python, R, Java, TensorFlow, and PyTorch for large-scale machine learning and deep learning models.
- Experience with AI/ML-driven demand forecasting, lead-time prediction, causal models, or fulfillment-rate prediction.
- Experience designing large-scale optimization solutions using decomposition methods, heuristics, metaheuristics, or hybrid methods.
- Familiarity with Spark, Hive, HBase, SQL/NoSQL, Redis, and MongoDB.
- Understanding of e-commerce and experience deploying advanced algorithms into production.
Culture & Benefits
- Interdisciplinary collaboration across product, engineering, business, and operations.
- Opportunity to contribute to ’s expansion in Taiwan and supply chain automation.
- Work includes an onsite or virtual onsite interview stage.
Hiring process
- Application review, phone interview, onsite or virtual onsite interview, and offer.
- Interview schedules and results are communicated by email.
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