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Sr . Global Analytics Hub Manager

4.00 to 6.00 Years   Delhi   31 Aug, 2019
Job LocationDelhi
EducationNot Mentioned
SalaryNot Disclosed
IndustryMedia / Dotcom / Entertainment
Functional AreaGeneral / Other Software
EmploymentTypeFull-time

Job Description

Data ManagementBuilding pipelines from different data sources to prepare core dataset for the engine to work onData prep and cleanup (missing data, outlier detection, duplications) from internet scale digital advertisement/ survey response dataData Integration (merge, join, subsetInsight GenerationMethodology writeups, interpretation of resultsApplications and generalization (Use cases, automation and scalability evaluation) POVs, 1- pager, vendor evaluation and assessmentTechnical ProgrammingCoding languages (Python is must, R is good to have) and Google tools (BigQuery, Airflow, GCP) Comfortable with data retrieval and processing with SQL and NoSQLSolid understanding of relational and non- relational database technology, data pipelineUnderstanding of code version management system A bit about yourself: Preferred: Knowledge of popular ad serving technologies and supporting analytical and research tools (Doubleclick, Atlas, comScore, Compete, etc. ) What you can expect from EssenceEssence 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. A degree in Engineering (Computer science is a plus) or equivalent fieldAt least 4- 6 years of industry experience in a data- focused roleExperience with managing multiple large data sources (structured or not) Ability to use the data to create a story and help create new analytical products or change an existing product in a way that improves company goals and metrics. Knowledge of the data science lifecycle - acquiring data from different sources, exploratory data analysis, scheduling tasks, creating and optimizing modes including validation and interpretation, and finally onward communication of results in a clear and succinct fashion. Hands- on Experience with programming languages (SQL, Python ) , statistical software packages (R, Python SciPy) would be a plus. Baseline understanding of all the five core competencies: programming, statistics, machine learning, data munging, and data visualization. Ability to communicate your findings effectively to non- technical audiences.,

Keyskills :
logistics delivery hubs management adserving datascience datamunging dataanalysis machinelearning dataintegration codinglanguages digitalmarketing nvent ymanagement expl at ydataanalysis vend evalua

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