
哈啰算法实习生-两轮研发
实习兼职技术地点:上海状态:招聘
任职要求
1. 学历背景:计算机科学、人工智能、数据科学、应用数学等相关专业硕士及以上学历; 2. 算法能力:具备扎实的机器/深度学习、数据挖掘、统计建模等相关算法知识,熟悉常用算法(如分类、回归、聚类、推荐算法等); 3. 编程能力:精通 Python 或 Java 等编程语言,熟悉常见的数据分析和机器学习框架(如 TensorFlow、PyTorch、scikit-learn、lightGBM 等); 4. 数据处理:熟悉 SQL,具有处理海量数据的经验,具备一定的数据清洗、特征工程能力; 5. 业务理解:有较强的业务敏感性,能够将复杂的业务问题转换为实际的算法解决方案; 6. 创新能力:具备良好的逻辑思维和创新能力,能够快速学习新技术并应用到实际工作中; 7. 沟通能力:具有良好的跨部门沟通协作能力,能够推动策略算法的实施与优化; 8. 经验要求:有策略算法相关领域(如风控、推荐、广告投放、金融策略等)的实际工作经验者优先。 加分项: ● 熟悉大模型、图算法、自然语言处理等前沿技术; ● 具有大规模分布式计算或高并发处理经验; ● 具有推荐系统、风控系统等大规模线上系统的设计和优化经验; ● 具备 A/B 测试、模型效果评估和调优的实践经验。
工作职责
1. 算法设计与优化:根据业务需求,设计并优化推荐、定价、风险控制等策略算法,提升业务决策效率和效果; 2. 数据分析与建模:通过分析海量数据,提取用户行为特征,构建机器学习模型,解决业务场景中的实际问题; 3. 策略调优与迭代:基于线上策略表现,进行模型调优和迭代优化,持续提升算法的精度和效果; 4. 跨部门协作:与产品、运营、工程等团队紧密合作,推动策略在业务中的落地与实现; 5. 模型监控与维护:搭建策略模型的监控体系,确保模型的稳定性和实时性,及时处理模型的偏差与异常; 6. 前沿技术探索:持续关注和研究行业前沿的算法技术,并应用于业务场景。
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
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/
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
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文,免费,零起点,完整示例,基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
Java+
https://www.youtube.com/watch?v=eIrMbAQSU34
Master Java – a must-have language for software development, Android apps, and more! ☕️ This beginner-friendly course takes you from basics to real coding skills.
数据分析+
[英文] Data Analyst Roadmap
https://roadmap.sh/data-analyst
Step by step guide to becoming an Data Analyst in 2025
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.
TensorFlow+
https://www.youtube.com/watch?v=tpCFfeUEGs8
Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
https://www.youtube.com/watch?v=ZUKz4125WNI
This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.
PyTorch+
https://datawhalechina.github.io/thorough-pytorch/
PyTorch是利用深度学习进行数据科学研究的重要工具,在灵活性、可读性和性能上都具备相当的优势,近年来已成为学术界实现深度学习算法最常用的框架。
https://www.youtube.com/watch?v=V_xro1bcAuA
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
Scikit-learn+
https://www.ibm.com/think/topics/scikit-learn
Scikit-learn, or sklearn, is an open source project and one of the most used machine learning (ML) libraries today.
https://www.youtube.com/watch?v=SIEaLBXr0rk
Today we to a crash course on Scikit-Learn, the go-to library in Python when it comes to traditional machine learning algorithms (i.e., not deep learning).
LightGBM+
https://lightgbm.readthedocs.io/en/stable/
LightGBM is a gradient boosting framework that uses tree based learning algorithms.
https://www.youtube.com/watch?v=tSZxOd1TWZc
In this video, we explore LightGBM, a machine learning algorithm developed by Microsoft that offers superior speed, efficiency, and accuracy.
SQL+
https://liaoxuefeng.com/books/sql/introduction/index.html
什么是SQL?简单地说,SQL就是访问和处理关系数据库的计算机标准语言。
https://sqlbolt.com/
Learn SQL with simple, interactive exercises.
https://www.youtube.com/watch?v=p3qvj9hO_Bo
In this video we will cover everything you need to know about SQL in only 60 minutes.
特征工程+
https://www.ibm.com/think/topics/feature-engineering
Feature engineering preprocesses raw data into a machine-readable format. It optimizes ML model performance by transforming and selecting relevant features.
https://www.kaggle.com/learn/feature-engineering
Better features make better models. Discover how to get the most out of your data.
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
NLP+
https://www.youtube.com/watch?v=fNxaJsNG3-s&list=PLQY2H8rRoyvzDbLUZkbudP-MFQZwNmU4S
Welcome to Zero to Hero for Natural Language Processing using TensorFlow!
https://www.youtube.com/watch?v=R-AG4-qZs1A&list=PLeo1K3hjS3uuvuAXhYjV2lMEShq2UYSwX
Natural Language Processing tutorial for beginners series in Python.
https://www.youtube.com/watch?v=rmVRLeJRkl4&list=PLoROMvodv4rMFqRtEuo6SGjY4XbRIVRd4
The foundations of the effective modern methods for deep learning applied to NLP.
高并发+
https://www.baeldung.com/concurrency-principles-patterns
In this tutorial, we’ll discuss some of the design principles and patterns that have been established over time to build highly concurrent applications.
https://www.baeldung.com/java-concurrency
Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.
https://www.oreilly.com/library/view/concurrency-in-go/9781491941294/
You’ll understand how Go chooses to model concurrency, what issues arise from this model, and how you can compose primitives within this model to solve problems.
https://www.oreilly.com/library/view/modern-concurrency-in/9781098165406/
With this book, you'll explore the transformative world of Java 21's key feature: virtual threads.
https://www.youtube.com/watch?v=qyM8Pi1KiiM
https://www.youtube.com/watch?v=wEsPL50Uiyo
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.
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