阿里巴巴数据分析师实习生
实习兼职阿里巴巴日常实习生地点:北京状态:招聘
任职要求
统计学、数学、计算机、经济学、运筹学等相关专业在校生,硕士优先;有互联网数据分析、商业分析、数据产品或策略分析相关实习经验者优先。 专业技能: 1.熟练掌握 SQL,能独立完成复杂查询、数据清洗与多表关联分析。 2.掌握 Python 或 R 至少一门分析语言,熟悉 Pandas、NumPy、Scipy 等常用数据分析库。 3.熟悉常用数据可视化工具(如 Tableau、FineBI、Quick BI 或 Python 可视化库),能将分析结论清晰呈现。 4.具备基本的统计学素养,理解假设检验、置信区间、回归分析、A/B 实验等常用方法。 5.了解数据仓库、ETL 流程及常用大数据组件(如 Hive、Spark SQL、MaxCompute)者优先。 软性…
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工作职责
1.参与 AI 应用的数据分析与效果评估,围绕智能推荐、搜索排序、LLM 应用等场景,构建分析框架并输出洞察,支撑产品迭代与业务决策。 2.参与商业智能指标体系建设,包括核心指标定义、口径梳理、数据看板搭建,推动 AI 应用效果的可度量、可归因、可追踪。 3.参与数据驱动的增长与优化,通过用户行为分析、漏斗拆解、A/B 实验设计与效果评估,发现业务增长机会点并验证 AI 策略效果。
包括英文材料
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
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.
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.
R+
[英文] R Tutorial
https://www.w3schools.com/r/
R is often used for statistical computing and graphical presentation to analyze and visualize data.
Pandas+
[英文] 10 minutes to pandas
https://pandas.pydata.org/docs/user_guide/10min.html
This is a short introduction to pandas, geared mainly for new users.
[英文] Cookbook - pandas
https://pandas.pydata.org/docs/user_guide/cookbook.html#cookbook
This is a repository for short and sweet examples and links for useful pandas recipes.
https://www.kaggle.com/learn/pandas
Solve short hands-on challenges to perfect your data manipulation skills.
https://www.youtube.com/watch?v=2uvysYbKdjM
I'm super excited for this one. We're doing another complete Python Pandas tutorial walkthrough.
https://www.youtube.com/watch?v=Mdq1WWSdUtw
Filtering, Joins, Indexing, Data Cleaning, Visualizations
NumPy+
https://numpy.org/doc/stable/user/absolute_beginners.html
NumPy (Numerical Python) is an open source Python library that’s widely used in science and engineering.
[英文] NumPy - Learn
https://numpy.org/learn/
Below is a curated collection of educational resources, both for self-learning and teaching others, developed by NumPy contributors and vetted by the community.
https://www.kaggle.com/code/themlphdstudent/learn-numpy-numpy-50-exercises-and-solution
This kernel uses exercises of NumPy from the Machine Learning Plus webpage
https://www.youtube.com/watch?v=KHoEbRH46Zk
If you've heard of Pandas and NumPy, you may think one is simply a superset of the other.
https://www.youtube.com/watch?v=QUT1VHiLmmI
Learn the basics of the NumPy library in this tutorial for beginners.
https://www.youtube.com/watch?v=VXU4LSAQDSc
This video serves as an introduction to the NumPy Python library.
Tableau+
https://help.tableau.com/current/guides/get-started-tutorial/zh-cn/get-started-tutorial-home.htm
了解如何连接到数据、创建数据可视化项、演示您的发现以及与其他人共享您的见解。
https://www.youtube.com/watch?v=K3pXnbniUcM
Spent 2 years creating a 21-hour, high-quality course that covers everything about Tableau.
数据仓库+
https://www.youtube.com/watch?v=9GVqKuTVANE
From Zero to Data Warehouse Hero: A Full SQL Project Walkthrough and Real Industry Experience!
https://www.youtube.com/watch?v=k4tK2ttdSDg
ETL+
https://www.ibm.com/think/topics/etl
ETL—meaning extract, transform, load—is a data integration process that combines, cleans and organizes data from multiple sources into a single, consistent data set for storage in a data warehouse, data lake or other target system.
https://www.youtube.com/watch?v=OW5OgsLpDCQ
It explains what ETL is and what it can do for you to improve your data analysis and productivity.
还有更多 •••
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