腾讯数据科学平台研发工程师(深圳/北京)
社招全职TEG技术地点：深圳状态：招聘
任职要求
1.硕士及以上学历，计算机科学、数据科学、统计学、应用数学等相关专业，掌握常用的统计学方法，熟悉常用的因果推断方法，熟练使用SQL、Python； 2.具备优秀的代码工程能力，精通java，熟悉spring cloud、k8s、微服务，服务治理； 3.熟悉DATA+AI，拥有工具类产品相关数据分析经验优先，熟悉databricks、dataiku、拥有Spark、Flink等平台的海量数据处理经验、拥有feast特征平台、triton推理框架等系统经验优先； 4.具有优秀的学习能力、沟通能力、团队合作意识；强烈的责任心与主动性，对所负责工作有owner意识，并能自我驱动成长。
工作职责
1.负责数据科学平台dataops+mlops+devops相关工具链(包括Notebook、数据标注、合成、特征、模型、推理、Agent应用等)的设计和开发工作； 2.负责优化系统架构，提升在线特征、推理等服务的性能和稳定性，提升研发质量和效率。
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
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.
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.
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.
Spring Cloud+
[英文] Spring Cloud Series
https://www.baeldung.com/spring-cloud-series
Learn Spring Cloud including concepts, additional libraries and examples for distributed systems.
Kubernetes+
https://kubernetes.io/docs/tutorials/kubernetes-basics/
This tutorial provides a walkthrough of the basics of the Kubernetes cluster orchestration system.
https://kubernetes.io/zh-cn/docs/tutorials/kubernetes-basics/
本教程介绍 Kubernetes 集群编排系统的基础知识。每个模块包含关于 Kubernetes 主要特性和概念的一些背景信息，还包括一个在线教程供你学习。
https://www.youtube.com/watch?v=s_o8dwzRlu4
Hands-On Kubernetes Tutorial | Learn Kubernetes in 1 Hour - Kubernetes Course for Beginners
https://www.youtube.com/watch?v=X48VuDVv0do
Full Kubernetes Tutorial | Kubernetes Course | Hands-on course with a lot of demos
微服务+
https://learn.microsoft.com/en-us/training/modules/dotnet-microservices/
Microservice applications are composed of small, independently versioned, and scalable customer-focused services that communicate with each other by using standard protocols and well-defined interfaces.
https://microservices.io/
Microservices - also known as the microservice architecture - is an architectural style that structures an application as a collection of two or more services.
https://spring.io/microservices
Building small, self-contained, ready to run applications can bring great flexibility and added resilience to your code.
https://www.ibm.com/think/topics/microservices
Microservices, or microservices architecture, is a cloud-native architectural approach in which a single application is composed of many loosely coupled and independently deployable smaller components or services.
https://www.youtube.com/watch?v=CqCDOosvZIk
https://www.youtube.com/watch?v=hmkF77F9TLw
Learn about software system design and microservices.
服务治理+
https://cloudnativecn.com/blog/istio-traffic-management-series-service-management-concept-theory/
通过阅读本文读者可以初步理解 Istio 流量治理的概念和相关知识框架。
https://juejin.cn/post/6844904006033080334
服务治理主要包括服务发现、负载均衡、限流、熔断、超时、重试、服务追踪等。我们今天要讲的，就是服务发现的内容。
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
Spark+
[英文] Learning Spark Book
https://pages.databricks.com/rs/094-YMS-629/images/LearningSpark2.0.pdf
This new edition has been updated to reflect Apache Spark’s evolution through Spark 2.x and Spark 3.0, including its expanded ecosystem of built-in and external data sources, machine learning, and streaming technologies with which Spark is tightly integrated.
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.
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