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讲座日程

5月7日（周二） 10:00-11:00

地点：中国传媒大学45号楼102

讲座主题

Do business analysis as a data scientist: from market and consumer aspects

数据科学在商业分析中的应用：市场和消费者行为分析

讲座简介

1. 什么是数据科学；

2. 成功的数据科学专家需要具备哪些技能；

3. 如何从学术研究进入到真正的数据科学工作领域；

4. 数据科学在市场和消费者行为领域分析中的应用；

5.开放式环节，数据科学领域相关问题讨论；

6. 数据科学家工作环境。

教授简介

Prof. Coggeshall

University of Southern California

• 南加利福尼亚大学马歇尔商学院教授

• 马歇尔商学院学生评价TOP3教授

• 美国著名商业数据科学家

• Morgan Stanley应用数据专家

• 美国三大国家实验室之一阿拉莫斯实验室资深研究员

• ID Analytics联合创始人、首席科学家（该公司成立于2002年，拥有全美最大的多行业消费者行为数据网络之一，为跨国公司进行业务风险评估和营销分析）

Curriculum Vita

Dr. Stephen Coggeshall is the retired Chief analytics and science officer at ID Analytics, an identity fraud protection company owned by LifeLock and Symantec. He was the founding CTO of ID Analytics where he built the analytics team and helped design the technical solution approach. Prior to ID Analytics Coggeshall worked for 11 years as a researcher in nuclear fusion at the Los Alamos National Laboratory. In addition to ID Analytics, Dr. Coggeshall also cofounded the analytics consulting companies CASA (acquired by HNC Software/FICO) and Los Alamos Computational Group (acquired by Morgan Stanley). His expertise is in forming and managing teams of data scientists to attack complex business problems using advanced algorithms on big data. He has deep expertise in consumer behavior modeling, optimization, forecasting and financial engineering, and spent the past 15 years focusing on identity fraud dynamics.

Dr. Coggeshall holds undergraduate degrees in math, music and physics. He has a master’s in music and a master’s and Ph.D. in nuclear engineering from the University of Illinois. He currently is a Professor at USC and UCSD teaching classes on Fraud Analytics and Business Analytics.

Lecture Topic

Do business analysis as a data scientist: from market and consumer aspects

Lecture Introduction

This presentation will cover a variety of topics that describe working as a data scientist in industry. First is an overview of what is data science with a brief description of some example applications in industry. Next is a discussion of the necessary skills and desired characteristics for a successful data scientist. The presentation then covers how one can enter this field, either as new student graduate or an experienced technologist from another discipline. Lastly is a discussion of the U.S. interview process and a description of a typical day-to-day environment for a data scientist working in industry.

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