Senior Data Scientist

Nielsen Sports

3 - 6 years

20 - 25 Lacs

bengaluru

Posted:15 hours ago| Platform:

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Skills Required

data analysis data science data reporting data collection manager technology hardware software quality design analysis

Work Mode

Work from Office

Job Type

Full Time

Job Description

Nielsen measures the media-consumption habits of homes globally. Our data paints a rich portrait of the audience in those markets we measure. As a pioneer and industry leader in audience measurement for more than half a century, we take pride in our technology and processes, and we are constantly searching for new ways to advance our culture of innovation and growth.
Our areas of expertise include researching hardware, software, quality controls and business rule changes that will improve the accuracy of our data reporting.
In this role, you will learn and become an expert in Nielsen s Panel data, with a focus on Meter hardware and software used for data collection and crediting. You will design analysis plans, develop underlying data pipelines, execute analyses and summarize results. You will collaborate with stakeholders across Data Science, Engineering, Product and Technology teams to provide clear data-driven recommendations based on research findings. Qualifications
- Implement, test and optimize econometric, and statistical models.
- Learn and become an expert in Audience Measurement, with a focus on digital meter technology used for data collection and crediting.
- Design analysis plans, develop underlying data pipelines, execute analyses and summarize results.
- Identify, clean, and summarize data, potentially from disparate and complex data sources, to facilitate high quality analyses.
- Create simple, meaningful visualizations to help support data analysis and stakeholder communications
- Develop and share efficient code used for analyses.
- Incorporate quality checks to proactively detect and correct for errors throughout analysis.
- Provide clear data-driven recommendations based on research findings.
- Collaborate with department stakeholders (Engineering, Data Science, Technology, etc). This includes providing status updates, developing timelines, sharing data, executing tests, presenting results, etc to ensure business needs are met.

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