Publicis Digital Lab (Saatchi & Saatchi) – Data Science Intern

Company
Publicis Digital Lab (Saatchi & Saatchi)
sg.leoburnett.com
Designation
Data Science Intern
Date Listed
16 Dec 2017
Job Type
Entry Level / Junior Executive
Intern/TS
Job Period
Immediate Start, For At Least 6 Months
Profession
IT / Information Technology
Industry
Others
Location Name
Central Business District (CBD), Raffles Place / Cityhall
Allowance / Remuneration
$700 - 850 monthly
Company Profile

Publicis Digital LAB applies analytic rigor, data-driven and fact-based reasoning to guide the development and execution of advertising and marketing strategies for clients. Specifically, we are aiming to use search, analytics, statistical modeling methodologies, machine learning and performance insight techniques to maximize the ROI of marketing and advertising across offline and digital channels. We seek entrepreneurial individuals with a background in business and marketing performance analysis and a passion for translating data into actionable insight.

Job Description

To support in strengthening the agency’s data-driven insights & strategy capabilities through science and technology. You will learn how to deliver meaningful insights rooted from data. You will help the digital lab team to facilitate quantitative and qualitative data analysis and visualisation by applying state-of-art data mining and machine-learning techniques.

Your responsibilities will include but not limited to:

  • Streamlining and automating the process of data gathering, cleaning and verifying the integrity of data used for analysis.
  • Writing simple scripts to scrap online data used for analysis.
  • Designing and creating proven and experimental data mining and machine-learning techniques to automate quantitative and qualitative data analysis. (this includes topic clustering, correlation, classification and sentiment analysis)
  • Building interactive dashboards that integrate various analytics capabilities including ecommerce, social, search, CRM etc using data visualisation tool.

Skills and Qualifications

  • Undergraduates pursuing a Degree in Econometrics, Physics, Biostatistics, Computer Science, Applied Mathematics. Engineering Data Mining, Machine Learning or a related quantitative discipline
  • Deep understanding and experience in data mining, machine-learning techniques, clustering, classification techniques and algorithms for both supervised and unsupervised learning.
  • Deep mathematics skills
  • Curiosity
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