Senior Data Analyst I

Role Summary As a Research Senior Data Analyst, you will bridge the gap between technical data processing and strategic insights. You will manage the end-to-end lifecycle of quantitative research, from scripting logic and AI-enhanced quality control to advanced statistical modeling and dashboarding. Key Responsibilities 1. Technical Design & Survey Scripting ● Advanced Scripting: Lead the programming of complex online surveys using Tivian, Decipher, Qualtrics, or in-house tools, ensuring sophisticated logic and seamless data collection. ● Study Implementation: Design and execute quantitative sports research studies, ranging from single-market ad-hoc projects to multi-country trackers. ● AI & Automation: Proactively utilize AI tools to enhance report quality, conduct rigorous Quality Control (QC), and standardize workflows to accelerate delivery speed. 2. Data Analysis & Statistical Modeling ● Analytical Rigor: Execute meticulous data cleaning, weighting, and tabulation. You serve as the final gatekeeper for the accuracy of tables and .sav files. ● Complex Modeling: Perform advanced analyses—including Regression, Segmentation, TURF, Conjoint, and MaxDiff—using SPSS, Q Research Software, or DisplayR. ● Insight Synthesis: Interpret disaggregated data to provide strategic recommendations that solve specific client business objectives. 3. Reporting & Visualization ● Dashboarding: Design and maintain dynamic visualizations and automated dashboards using Power BI or Display R. ● Strategic Collaboration: Partner with senior researchers to interpret data and craft high-impact client reports and presentations. 4. Agile Project & Stakeholder Management ● Multi-Project Handling: Independently manage the analytical workstreams for multiple projects simultaneously, ensuring all data is delivered on time and within budget. ● Stakeholder Liaison: Interact with diverse internal and external stakeholders across the global Nielsen network to ensure project alignment and technical excellence.

Who You Are ● Experience: 4–7 years in market research or data analytics, with a heavy focus on quantitative methodologies. ● Sports Enthusiast: You live and breathe sports. You understand the nuances of international events, teams, leagues, and the economics of sponsorship. ● Technical Mindset: You are a proactive problem-solver who thinks laterally and thrives in an agile, dynamic team environment. ● Education: Bachelor’s degree or higher in a subject requiring advanced mathematical analysis and high-level communication skills. Technical Toolkit Category Skills & Tools Statistical Software - SPSS, Q Research Software, or DisplayR Survey Scripting - Tivian, Decipher, Qualtrics, or similar enterprise platforms Visualization - Power BI, DisplayR or Tableau Data Mastery - Expert Excel (Pivot tables, Macros, Advanced Formulae) Programming (Plus) SQL, R, or Python The Winning Edge (Preferred) ● AI Certification: A recognized certification in Artificial Intelligence or Machine Learning is a significant advantage. ● Project Tools: Familiarity with Monday.com for capacity planning and project tracking.

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