Senior Data Scientist II at TheNielsenCompany

Nielsen is seeking a strategic and analytical Senior Data Scientist / Senior Decision Scientist to lead the technical execution and analysis of our Customer Experience research. In this role, you will lead the analytical strategy of our flagship semi-annual Client Satisfaction Survey - informing the design to ensure data quality and leading the deep-dive analysis that follows and more broadly you will serve as the bridge between raw data and business strategy. We are looking for a candidate who can apply rigorous research methods to inform survey design, integrate that feedback with internal product and usage data, and build predictive models to inform decision-making for Nielsen’s senior leadership. Responsibilities Predictive Modeling & Advanced Analysis • Driver Analysis: Build statistical models to identify the key drivers of Customer Experience metrics (NPS, CSAT, CES). You will determine which specific operational factors (e.g., product speed, support response time) have the highest impact on client sentiment. • Client Health Modeling: Design and build a comprehensive "Client Health" model. You will determine the weighting of various inputs (survey scores, product usage, support tickets) to create a robust picture of account health across our Product portfolio. • Retention & Dissatisfaction Analysis: Develop statistical models to predict retention risks. You will analyze historical data to identify early warning signs of dissatisfaction and link them to specific operational or product factors. • Behavioral Linkage: Go beyond isolated survey scores by quantifying the relationship between what clients do (telemetry/usage) and how they feel (sentiment), creating a holistic view of the Customer Experience. Survey Strategy & Design Influence • Design Strategy: Partner with the survey operations team to inform the questionnaire design. You will ensure the instrument captures the specific predictive signals and psychographic variables needed to power your retention and health models. • Statistical Rigor: Advise on sampling frames and statistical weighting methodologies. You will provide the technical oversight to ensure the data collected is accurate and representative of Nielsen’s diverse client base. • Instrument Optimization: Review and recommend evolutions to the survey instrument, ensuring it allows for year-over-year trend analysis while adapting to new modeling requirements. Insights Management & Presentation • Executive Reporting: Translate complex models and datasets into clear, visual executive summaries. You should feel comfortable presenting results to all levels of leadership when required. • Stakeholder Engagement: Collaborate with Commercial, Product, and Tech teams to help them understand the data. You will be the "go-to" expert when leaders have questions about the methodology or specific findings. • Actionable Recommendations: Move beyond reporting the numbers by providing data-backed recommendations on where the business should focus to improve the Customer Experience.