滴滴26届正式批-营销算法工程师(金融)
校招全职算法类地点:北京状态:招聘
任职要求
1、2026届毕业生,硕士及以上学历,计算机、数据科学、统计学、应用数学等相关专业优先,有机器学习、推荐系统、优化算法、因果推断、运筹优化等相关知识储备 2、具备扎实的算法基础,熟悉常见的机器学习/深度学习算法,如 LR、XGBoost、DeepFM、Transformer、LSTM 等,并能根据业务需求进行模型优化 3、熟悉 Python/Java/C++,掌握 TensorFlow…
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工作职责
1、用户增长算法优化:基于滴滴金融信贷业务,通过多种触达渠道,实现高效用户拉新和促活,提升渠道转化率 2、精准营销策略优化:基于用户画像、用户行为数据,构建用户意愿预测模型、个性化推荐模型、触达优化模型,提升营销精准度 3、渠道投放优化:构建 CTR/CVR 预测模型、智能投放策略,提升营销投放 ROI,降低无效触达 4、大模型/AI 赋能营销:探索大模型(NLP、AIGC)在短信内容生成、AI 外呼话术优化、用户情绪识别等场景的应用,提升触达效率与用户体验 5、数据分析与策略迭代:通过 A/B 测试、因果推断等方法,评估不同策略的效果,推动算法和策略迭代优化。
包括英文材料
学历+
数据科学+
https://roadmap.sh/ai-data-scientist
Step by step roadmap guide to becoming an AI and Data Scientist
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.
推荐系统+
[英文] Recommender Systems
https://www.d2l.ai/chapter_recommender-systems/index.html
Recommender systems are widely employed in industry and are ubiquitous in our daily lives.
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/
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.
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.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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.
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
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