神州数码26届校招-集团英才-CBG算法工程师(J21146)
校招全职地点：北京状态：招聘
任职要求
1. **专业背景**：硕士及以上学历，计算机、统计学、数学、人工智能相关专业。 2. **经验要求**：数据分析/算法开发实习经验，熟悉大数据技术栈。 3. **技能要求**： - 精通Python/SQL，熟练使用主流分析工具（Pandas、PySpark、BI工具等）； - 掌握机器学习框架（Scikit-learn、TensorFlow/PyTorch）及算法优化方法； - 熟悉数据仓库（如Hive、ClickHouse）与大数据平台（如Hadoop、Flink）； - 具备业务理解能力，能将分析结果转化为可落地的业务策略。 4.**加分项**： 有AIGC应用经验（如LLM微调、RAG系统开发）；
工作职责
1. 基于业务场景设计数据分析模型（如用户画像、运营分析、风险预警），输出数据洞察报告。 2.开发数据挖掘与机器学习算法（如分类、聚类、预测模型），支持业务智能化决策。 3. 参与数据清洗、特征工程、模型训练与调优，推动算法落地到生产环境。 4.探索前沿技术（如AIGC、图计算）在业务场景中的应用可能性。
包括英文材料
学历+
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
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/
大数据+
https://www.youtube.com/watch?v=bAyrObl7TYE
https://www.youtube.com/watch?v=H4bf_uuMC-g
With all this talk of Big Data, we got Rebecca Tickle to explain just what makes data into Big Data.
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.
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.
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
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.
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).
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.
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
Hive+
[英文] Hive Tutorial
https://www.tutorialspoint.com/hive/index.htm
Hive is a data warehouse infrastructure tool to process structured data in Hadoop. It resides on top of Hadoop to summarize Big Data, and makes querying and analyzing easy.
https://www.youtube.com/watch?v=D4HqQ8-Ja9Y
ClickHouse+
[英文] Advanced Tutorial
https://clickhouse.com/docs/tutorial
Learn how to ingest and query data in ClickHouse using the New York City taxi example dataset.
https://www.youtube.com/watch?v=FtoWGT7kS-c
ClickHouse is an open-source column-oriented DBMS for online analytical processing that allows users to generate analytical reports using SQL queries in real-time.
https://www.youtube.com/watch?v=Rhe-kUyrFUE&list=PL0Z2YDlm0b3gcY5R_MUo4fT5bPqUQ66ep
Hadoop+
https://www.runoob.com/w3cnote/hadoop-tutorial.html
Hadoop 为庞大的计算机集群提供可靠的、可伸缩的应用层计算和存储支持，它允许使用简单的编程模型跨计算机群集分布式处理大型数据集，并且支持在单台计算机到几千台计算机之间进行扩展。
[英文] Hadoop Tutorial
https://www.tutorialspoint.com/hadoop/index.htm
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models.
Flink+
https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/learn-flink/overview/
This training presents an introduction to Apache Flink that includes just enough to get you started writing scalable streaming ETL, analytics, and event-driven applications, while leaving out a lot of (ultimately important) details.
https://www.youtube.com/watch?v=WajYe9iA2Uk&list=PLa7VYi0yPIH2GTo3vRtX8w9tgNTTyYSux
Today’s businesses are increasingly software-defined, and their business processes are being automated. Whether it’s orders and shipments, or downloads and clicks, business events can always be streamed. Flink can be used to manipulate, process, and react to these streaming events as they occur.
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
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
相关职位
校招
1.大模型微调与优化 基于业务场景需求，主导7B/14B等参数量级大模型的微调全流程，涵盖数据清洗、算法选择（如LoRA/QLoRA）、量化压缩（INT4/INT8）及部署优化 设计参数高效微调方案，优化模型推理效率与成本，推动RAG技术栈（向量数据库/检索增强）在业务中的落地 跟踪前沿技术（如Diffusion模型、多模态微调），探索模型轻量化与领域适配的创新方案 2.AI Agent开发与系统集成 构建基于LLM的智能体架构，实现任务规划、记忆管理、工具调用等核心功能，开发符合业务逻辑的Agent交互系统 集成LangChain、LlamaIndex等开发框架，实现AutoGPT式自主决策能力，优化Agent在复杂场景下的鲁棒性 推动Agent与数字孪生、数字员工等技术的融合，提升工业检测、智能客服等场景的自动化水平 3.客户需求转化与方案落地 深度参与客户需求分析，将业务场景（如制造、金融、医疗）转化为可执行的AI技术方案，提供端到端咨询服务 输出技术文档与API接口，支持跨部门协作与客户侧的技术培训 监控模型生产环境表现，针对客户反馈持续迭代优化，确保SLA达成与成本可控
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