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Quantitative Analyst, Operations Research and Optimization
2 months ago
Are you passionate about leveraging your quantitative analysis and big data expertise to tackle significant challenges? Do you have an interest in developing methodologies, models, and systems for strategic planning, logistics, and fulfillment networks? If this resonates with you, we invite you to explore this opportunity.
About the Team: Our team, Analytics Technology and Engineering (ATE), is seeking a Data Scientist to join our expanding Science Team.
We focus on establishing core analytics technology capabilities, developing quantitative models, and enhancing data engineering processes. Our mission is to create scalable analytics applications and research models that optimize operational workflows.
We standardize and refine data sources and visualization efforts across various regions, while also building and maintaining comprehensive business intelligence services and data repositories.
Your Role: You will collaborate with fellow scientists, data engineers, business intelligence engineers, and product managers, employing rigorous quantitative methods to deliver high-quality data technology products for our global clientele.
As part of a rapidly growing organization, your primary focus will be on developing strategic models and automation tools that utilize our extensive data resources to enhance operational efficiency.
You will be tasked with constructing models and tools that improve the economics of our global fulfillment networks, ultimately increasing delivery speed and reducing operational costs.
Your responsibilities will include:
- Designing and developing intricate mathematical, simulation, and optimization models to address strategic and tactical requirements.
- Applying mathematical optimization theories to create optimal or near-optimal solution methodologies for internal decision support tools.
- Translating business inquiries into specific analytical questions that can be addressed using available data through statistical and machine learning techniques.
- Prototyping models using programming languages and efficient data querying infrastructures.
- Effectively communicating proposals and results, supported by data, to drive informed business decisions.
- Collaborating with colleagues from diverse scientific, engineering, and business disciplines.
- Managing your own workflow, prioritizing impactful projects, and ensuring timely delivery.
Basic Qualifications:
- Ph.D. or Master's degree (with 4+ years of industry experience) in Operations Research, Industrial Engineering, Applied Mathematics, Machine Learning, Statistics, Computer Science, or a related quantitative field.
- Hands-on experience with programming languages such as Python, Java, or C++.
- Ability to convey complex mathematical concepts to non-technical stakeholders.
- Strong skills in clarifying and formalizing intricate problems.
- Excellent verbal and written communication skills in both Chinese and English.
Preferred Qualifications:
- Experience with large-scale optimization and decomposition techniques.
- Practical experience applying machine learning to solve complex real-world problems.
- Significant contributions to peer-reviewed scientific literature.
- Strong foundational knowledge in computer science, including data structures and algorithm design.
