Senior Executive - Analytics (Marketing Mix Model)
at World's largest Media Investment Company
Data Analytics
PythonSenior Executive - Analytics
Overview of job :-
Our Client is the world’s largest media investment company which is a part of WPP. They are a global digital transformation agency with 1200 employees across 21 nations. Our team of experts support clients in programmatic, social, paid search, analytics, technology, organic search, affiliate marketing, e-commerce and across traditional channels.
We are currently looking for a Sr Executive – Analytics to join us. In this role, you will be responsible for a massive opportunity to build and be a part of largest performance marketing setup APAC is committed to fostering a culture of diversity and inclusion. Our people are our strength so we respect and nurture their individual talent and potential.
Reporting of the role - This role reports to the Director - Analytics,
3 best things about the job:
1. Responsible for data & analytics projects and developing data strategies by diving into data and extrapolating insights and providing guidance to clients
2. Build and be a part of a dynamic team
3. Being part of a global organisations with rapid growth opportunities
Responsibilities of the role:
Build Marketing-Mix and Multi-Touch attribution models using a range of tools, including free and paid.
Work with large data sets via hands-on data processing to produce structured data sets for analysis.
Design and build Visualization, Dashboard and reports for both Internal and external clients using Tableau, Power BI, Datorama or R Shiny/Python.
What you will need:
Degree in Mathematics, Statistics, Economics, Engineering, Data Science, Computer Science or quantitative field.
2-3 years’ experience in Marketing/Data Analytics or related field with hands-on experience in building Marketing-Mix and Attribution models. Proficiency in one or more coding languages – preferred languages: Python, R
Proficiency in one or more Visualization Tools – Tableau, Datorama, Power BI
Proficiency in using SQL.
Proficiency with one or more statistical tools is a plus – Example: SPSS, SAS, MATLAB, Mathcad.
Working experience using big data technologies (Hive/Hadoop) is a plus
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