Data Scientist
Confirmed on the employer's own hiring board on Oct 3, 2026. First seen by Alion on Oct 1, 2026. Nielsen scores B on the Alion truth index.
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.
Our team develops new techniques and processes to better meet the needs of our Audio and TV clients to measure audiences, working at the intersection of Data Science, Technology, Product Delivery and Operations.
In this role, you will be working on the forecasting, modeling and code which drive the key production processes of the PPM Wearables audience measurement panels. You will develop data pipelines, execute analyses and summarize results, collaborating with a variety of stakeholders to provide clear data-driven solutions and recommendations.
Responsibilities
Research, design, develop, implement and test econometric, statistical, optimization and machine learning models.
Gain a deep understanding of the PPM (Portable People Meter) sampling methodology and become an expert in Audience Measurement, with a focus on panel management strategies.
Query data from large relational databases for various analyses and/or requests.
Utilize tools such as Python, Tableau, R etc. to perform complex data analysis and visualizations.
Oversee, maintain and evolve multiple data algorithms for managing the PPM Sample Methodology in a time-critical production environment.
Maintain and update documented departmental procedures, checklists and metrics comprehensively and on a timely basis.
Serve on various interdepartmental teams seeking to propose, evaluate and implement new initiatives, and work on other critical projects. This includes support with writing requirements, developing new software and testing.
Respond to various internal and external client requests, providing data driven solutions to the problems presented.
Incorporate quality checks to proactively detect and correct for errors throughout production processing and analysis.
Ensure product quality, stability, and scalability by facilitating code reviews and driving best practices like modular code, unit tests, and incorporating CI/CD workflows.
Bachelor’s Degree or higher in Mathematics, Statistics, Computer Science, Data Science, Data Engineering or a related field.
3+ years of professional work experience in Statistics, Data Science, and/or related disciplines, with focus on delivering analytical software solutions in a production environment.
3+ years of experience with the following:
Manipulating, analyzing and interpreting complex data sources to tell a story from data through analyses
Programming in Python, PySpark and SQL for data pipeline development used to support analytics
Data visualization with Tableau and/or similar tools
Experience working in cloud-based environments such as AWS
DevOps tools, code management and CI/CD workflows using Gitlab or similar tools
Project management including ability to prioritize multiple assignments
Well-organized, clear communication, and an ability to handle multiple competing priorities in a fast-paced environment.
Embraces innovation with a readiness to explore new solutions and a commitment to rapid iteration based on customer feedback.
Demonstrates strategic thinking, understanding the broader impact of data insights on product and business objectives.
Exceptional problem solving skills. Abilities to solve problems independently and within a cross-functional team to resolve issues in the projects.
Nice to have: Working Knowledge of statistical tests and procedures such as ANOVA, Chi-squared, Correlation, Regression, and Student t-test.
Expertise in querying large datasets with SQL and of working with Oracle/Netezza/Data Warehouse and Data Lake data structures.
Critical thinking skills to evaluate results in order to make timely decisions.
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