Dentsu Aegis Network
Data Science Analyst Intern
16 Aug 2019
Dentsu Aegis Network Ltd. is a multinational media and digital marketing communications company headquartered in London, United Kingdom, and a wholly owned subsidiary of the Japanese advertising and public relations firm Dentsu. Its principal services are communications strategy through digital creative execution, media planning and buying, sports marketing and content creation, brand tracking and marketing analytics. It is organised into ten main divisions: Carat, Dentsu (operations outside Japan), Dentsu media, mcgarrybowen, Merkle, MKTG, Posterscope, Isobar, iProspect and Vizeum. Dentsu Aegis Network manages all the Dentsu inc. owned businesses outside the Japan market, which includes the former Aegis Group business that it acquired in 2013. It also includes 360i, Amplifi, Amnet, BJL, The StoryLab, Data2Decisions, Mitchell Communications, Cardinal Path and psLIVE. It has 35,000 people across 145 countries.
As a Data Science Analyst, you will work closely with the Data Scientists and the engineering team to develop leading edge data analytics solutions and capabilities that uncovers insights from vast amounts of structured and unstructured data, through a combination of research and experimentation.
Key responsibilities and accountabilities: (or ‘Duties’)
• Apply quantitative methods and build statistically valid and scalable algorithms that convert actionable conclusions from very large data sets.
• Able to synthesize scientific publications on statistical applications and then write programs to implement the applicants
• Complete tasks effectively and in a timely manner
• Diploma from Polytechnic and/or University degree and/or Postgraduate degree
• One-year bachelor’s degree in Mathematics, Statistics, Computer Science, Engineering or Information Systems
• Familiar with Python programming, including pandas and NumPy libraries
• Good understanding of statistics and numerical analysis techniques
• Working knowledge in machine learning / data mining
• High logical systematic, self-motivated and collaborative
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