PDA(Portal and Data Analytics) team负责Cisco协作产品大数据分析平台的设计与建设; 并基于客户、 产品设计者、管理者、工程师团队等的不同需求，分析客户的使用、服务的质量、产品的运行情况等，为业务决策提供科学的数据分析支持。

• •跨团队合作，理解业务与业务模型
• •利用Machine learning技术，选取特征，建立并优化分类器
• •建立数据分析、Machine learning的模型和算法
• •利用前沿的方法进行数据挖掘
• •与团队共同优化数据处理与清洗，验证用于分析数据的完整性
• •做特定的数据分析，清晰地汇报结果
• •建立自动化的异常侦测系统和持续的性能跟踪
• •建立相应的技术文档

职位要求:

• 符合或者接近以下需求

  基本需求：数学、计算机科学、软件工程、信息管理或统计相关专业研究生o对大数据技术领域有强烈的兴趣o良好的书面与口头英语沟通能力。

  技术需求：深入理解Machine learning的技术与算法，如k-NN, Na?ve Bayes, SVM, Decision Forests等o掌握常用数据科学工具的或有相关的使用经验，如R, MatLab等.o掌握数据可视化工具的使用o熟悉数据查询语言，如SQL, Hive, Pigo具有NoSQL数据库的知识或使用经验，如HBase, Cassandrao掌握良好的应用统计学技能，如分布、统计检验、回归等o掌握良好的脚本编程技能，如Pythono面向数据的思维。

  
  

  
  

  Department introduction:PDA (Portal and Data Analytics) team is responsible for designing and building Cisco collaboration product data analytics platform. Meanwhile, based on various requirements from customer, product management, executive and engineering teams, we make usage data, quality data and operation data analytics to drive business by data science.
• Responsibilities:Work along with cross functional teams to understand business and its modelsSelect features, build and optimize classifiers using machine learning techniquesCreate data analytics, machine learning models and algorithmsData mining using state-of-the-art methodsWork along with team to enhance data processing and cleansing, and verify the integrity of data used for analysisDo ad-hoc analysis and present results in a clear mannerCreate automated anomaly detection systems and constant tracking of its performanceCreate relevant technical documents
• Requirements: Meet or be high potential for the below requirementsCommon requirementsoMaster degree in Mathematics, Computer Science, Software engineering, Information Management or StatisticsoIntense interest in big data technology area.oGood written and verbal English communication skillsTechnical requirementsoExcellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.oKnowledge of or experience with common data science toolkits, such as R, MatLab, etc. Excellence in at least one of these is highly desirableoExperience with data visualization toolsoProficiency in using query languages such as SQL, Hive, PigoExperience with NoSQL databases, such as HBase, CassandraoGood applied statistics skills, such as distributions, statistical testing, regression, etc.oGood scripting and programming skills, such as PythonoData-oriented personality

Hangzhou