Data Analyst

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 DescriptionWe are seeking a talented Data Analyst that has a passion for working with data, backed with strong creativity and discipline. As a Data Analyst, you will play a critical role in delivering first-class evaluations and measurement options based on data to support client decision making in a reliable and efficient manner.  Investing in proper data analysis at the onset of a project is key for successful delivery overall.

Responsabilities

• Collaborates with Analytics team and Modeling associates within Marketing Mix project teams
• Collects and analyzes significant amounts of data for quality, accuracy, and fitness of purpose
• Integrates, assembles, summarizes, validates, and disseminates data from numerous disparate systems (flat files, spreadsheets, relational databases, etc.) to present measurement recommendations to client
• Identifies anomalies within the data and helps determine if it is a collection error or an unnoticed trend

Skills

• High proficiency in English
• Strong analytical aptitude
• Proven problem-solving skills using deductive reasoning, understanding hierarchical relationships and identifying gaps in logic
• Demonstrated project management skills and ability to manage multiple priorities and deadlines
• Proficiency in Microsoft Office (Excel, PowerPoint) and Google applications
• Attention to detail when working with small and large data volumes
• Working knowledge of statistical languages (e.g., R, Python, SQL, SAS) is a plus

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