饿了么饿了么-机器学习算法专家(营销定价机制)-上海
社招全职2年以上技术类-算法地点:上海状态:招聘
任职要求
1. 计算机、运筹学、应用数学、统计学或相关专业,有算法领域的工作经验; 2. 熟悉机器学习/深度学习/数据挖掘/运筹优化中至少一个领域的原理与算法,并且能够熟练建模解决业务问题; 3. 在一个或多个营销子领域的常用模型和架构上有丰富的经验和深入的理解,包括但不限于: ⁃ 模型预估方向:熟悉常用机器学习算法,如FM、DeepFM、XGBoost、DNN、GNN等,结合营销场景设计uplift model及因果推断模型 ⁃ 运筹决策方向:熟悉常用运筹优化算法,如线性规划、动态规划、整数规划、二次/随机规划等,熟悉最优化离线/在线求解理论 ⁃ 量价模型方向:熟悉常用选品定价算法,如商品知识图谱、量价模型、价格管控、价格联动机制等 4. 具有优秀的分析和解决问题的能力; 5. 良好的团队合作精神和沟通能力。
工作职责
1. 负责饿了么营销定价机制算法,包括补贴定价、商品定价,以及店品价格机制、定价和供给物流联动机制等; 2. 负责营销定价、商家供给、物流运力的三端联动,助力业务的规模增长; 3. 参与营销创新性算法的研究及开发工作; 4. 协同业务进行跨团队合作。
包括英文材料
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
数据挖掘+
https://www.youtube.com/watch?v=-bSkREem8dM
Database vs Data Warehouse vs Data Lake
https://www.youtube.com/watch?v=7rs0i-9nOjo
运筹优化+
https://medium.com/gousto-engineering-techbrunch/an-introduction-to-operations-research-5a9e898b6c60
Operations research (OR) is a scientific approach to determining the optimal solution to a defined business problem.
DeepFM+
https://d2l.ai/chapter_recommender-systems/deepfm.html
DeepFM consists of an FM component and a deep component which are integrated in a parallel structure.
https://deeprs-tutorial.github.io/WWW_DNN.pdf
XGBoost+
[英文] What is XGBoost?
https://www.ibm.com/think/topics/xgboost
XGBoost (eXtreme Gradient Boosting) is a distributed, open-source machine learning library that uses gradient boosted decision trees, a supervised learning boosting algorithm that makes use of gradient descent.
https://www.youtube.com/watch?v=BJXt-WdeJJo
takes a deep dive into one of the most powerful machine learning algorithm, eXtreme Gradient Boosting, using a Jupyter notebook with Python.
GNN+
https://distill.pub/2021/gnn-intro/
Neural networks have been adapted to leverage the structure and properties of graphs.
https://gnn.seas.upenn.edu/
Graph Neural Networks (GNNs) are information processing architectures for signals supported on graphs.
https://www.ibm.com/think/topics/graph-neural-network
Graph neural networks (GNNs) are a deep neural network architecture that is popular both in practical applications and cutting-edge machine learning research.
因果推断+
https://web.stanford.edu/~swager/causal_inf_book.pdf
How best to understand and characterize causality is an age-old question in philosophy.
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