About Essence

Essence, part of GroupM, is a global data and measurement-driven agency whose mission is to make advertising more valuable to the world. Clients include Google, Flipkart, Nando's and the Financial Times. The agency is more than 1,600 people strong, manages over $3.6B in annualized media spend and deploys campaigns in 71 markets via its global offices throughout North America, EMEA and APAC.

Visit essenceglobal.com for more information and follow us on Twitter at @essenceglobal.

About the role

Essence is known for its use of data and rigorous experiment-based best practices to measure and quantify the success of digital media. Over the years, we have run hundreds of studies and led several research and analytics projects to understand what makes digital advertising successful.

This role is a member of a team that is in charge of building a predictive planning engine capable of leveraging all the data we've aggregated over the years. You will be instrumental in the evolution of this vital initiative by looking for solution in Essence's terabyte scale data. This role offers the perfect blend of data engineering and digital analytics expertise for an aspiring data engineer with an entrepreneurial spirit.

Some of the things we'd like you to do:

* Data prep and cleanup (missing data, outlier detection, duplications) from internet scale digital advertisement/survey response data
* Data integration (merge*, join*, subset*)
* Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing data infrastructure for greater scalability, data quality and performance etc.
* Build the data infrastructure, tools, and processes that enable our teams to rapidly and reliably build reproducible and effective pipelines, reports, analyses, and models.
* Work closely with your peers within analytics team (Data Scientists, ML Engineers, Data Analysts) as well as in other practices at Essence (e.g. performance marketing, media buying and planning etc.), to ensure data engineering and platform support for various phases of our campaigns.
* Producing data visualization (Tableau, DataStudio etc.) for interactive analysis

Technical Programming

* Fluent with Internet-scale data retrieval and processing with SQL and NoSQL
* Comfortable in coding languages (Python*/Java), and Google tools (BigQuery*) for data processing and transformation
* Understanding of relational and non-relational database technology
* Familiarity with cloud-based data lake, ETL, data pipeline
* Understanding of code version management system(Github)

A bit about yourself:

* Degree/equivalent experiences in the applied quantitative field (Statistics, Mathematics, Engineering or CS).
* Some industry experience ( or a graduate degree) in a data-focused role
* Knowledge of the data science lifecycle - acquiring data from different sources, exploratory data analysis, creating and optimizing modes including validation and interpretation, and finally onward communication of results in a clear and succinct fashion.
* Hands-on Experience with data pipeline building, ETL
* Experience in Big Data technologies
* Good understanding of data architecture, data integrity concepts and data standardization.
* Experience in Google Cloud/AWS technologies is a plus
* Experience with digital marketing ecosystem is a big plus

What you can expect from Essence

Essence's mission is to make advertising more valuable to the world. We do this by employing the world's very best talent to solve some of the toughest challenges of today's digital marketing landscape. It's important that we hire people whose values reflect those of our own: genuine, results-focused, daring and insightful. As an Essence employee, we promise you a workplace that invests in your career, cares for you and is fun and engaging. We believe these factors create a workplace where you can be yourself and do amazing work.



* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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