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.

About the Role

This job description outlines the responsibilities and qualifications for an AI / ML Data Scientist II role with a primary focus on designing, building, and deploying scalable machine learning systems, software engineering best practices, and the application of AI/ML principles within Machine Learning and Data Science contexts.

Audience is everything! Nielsen offers the world's most complete measurement of media-viewing behavior. Our data scientists and ML engineers leverage the best data assets and modeling methods to build consistent and comparable metrics of the media landscape in multiple countries. We help the world's biggest brands make better and faster media and marketing decisions.

Responsibilities

• Implement, test, and optimize econometric, statistical, and Machine Learning (ML) models to enhance data accuracy and reporting.
• Identified the AI opportunities in existing and new projects and implemented them.
• Quickly learn and become an expert in Audience Measurement and the associated digital meter technology for data collection.
• Design comprehensive ML workflows, develop reliable data pipelines (using Databricks/AWS S3), execute sophisticated model training and evaluation, and clearly summarize results.
• Identify, integrate, clean, and transform data from disparate and complex data sources to ensure high-quality inputs for ML models.
• Develop, share, and maintain efficient, well-documented, production-quality code following software engineering best practices.
• Proactively incorporate quality checks throughout the ML development lifecycle to detect and correct errors swiftly.
• Create simple, meaningful visualizations (e.g., using Tableau) to effectively support data analysis and clearly communicate insights and findings to stakeholders.
• Translate complex research findings into clear, data-driven recommendations that address business needs and drive product/technology improvements.
• Partner closely with department stakeholders (Engineering, Data Science, Product, Technology) to manage timelines, share data, execute tests, and present results.

Key Skills & Qualifications

• Bachelor’s Degree or higher in Mathematics, Statistics, Computer Science, Data Science, Data Engineering, or a closely related quantitative field.
• 3-6 years of professional experience in a Data Engineer or similar quantitative role.
• Proven ability to manipulate, analyze, and interpret complex data sources to effectively "tell a story from data" through impactful analyses.
• Proficiency in Python, PySpark, SQL, Artificial intelligence and Machine learning
• Deep understanding and application of Statistics, including hypothesis testing, regression analysis, and experimental design.
• Experience with trending and visualizing data using tools like Tableau
• Familiarity with Media Data Lake (MDL) concepts is a plus.

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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