Job Description

Company Description

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future.

Job Description

What will I do?

Build measurement and planning solutions for publishers, advertisers, and agencies.
Identified the AI opportunities in existing and new projects and implemented them.
Support reproducible data science projects end-to-end
Deploy and maintain data pipelines and models in a production environment
Work with cross-functional teams to productionize, validate, and optimize methodologies
Communicate methodology and research findings to varying audiences
Support research on methodology changes to cross-platform audience measurement. The primary research areas include trend analyses, imputing missing data, representation/ sampling, bias reduction, indirect estimation, data integration, and automation.
Continuous support and development of new projects by exploring the data - Variable Identification, cleaning the data , applying dimension reduction techniques, calculating distances and integrating the surveys. And also using output evaluation techniques in order to make sure of the accuracy.
Address quality escapes and fix issues in production code.
Document new methodologies and code.

Qualifications

Responsibilities:

0-3 years work experience
Proficiency in Python, Spark, SQL, Artificial intelligence and Machine learning
Degree in data science, statistics, engineering, applied mathematics, operations research, information sciences, or another biological/physical science.
Strength in code documentation
Proficiency in Git and code versioning tools (Gitlab)
Proficiency in Atlassian Suite such as JIRA and Confluence.
Familiarity with cloud computing (AWS, Goolge Cloud preferred)
Knowledge of statistics and machine learning
Ability to manipulate, analyze, and interpret large datasets
Knowledge of dashboarding and visualization tools like Spotfire/Tableau.

Additional Information

Business Skills:

Excellent oral and written communication
Self-motivation and an ability to handle multiple competing priorities in a fast-paced environment
Strong interpersonal skills and the ability to develop effective relationships with other team members, including remotely.

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