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. Qualifications

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.