Senior Data Scientist I

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

The Senior Data Analyst I develops analytic solutions that provide transparency to and enable critical business decisions regarding panel health, sample performance, and operational efficiency. In this role, you will apply a strong mathematical and statistical background to build predictive and prescriptive models aimed at optimizing operational spending—specifically reducing panelist incentives and operational costs without impacting panel performance, data quality, or core KPIs. Additionally, you will play a key role in tool migration initiatives, decoding complex logic from legacy workflows and data pipelines and re-engineering them into modern analytics frameworks. The ideal candidate brings 5+ years of experience, exhibits excellent project leadership skills, and communicates complex statistical insights clearly across technical and non-technical stakeholders.

Key Responsibilities

• Statistical Modeling & Cost Optimization: Apply advanced statistical methods, rate forecasting, and predictive modeling to identify cost-saving opportunities across panel operations, specifically driving reductions in panelist incentive costs while maintaining data integrity and key performance metrics.
• Tool Migration & Logic Decoding: Work closely with stakeholders to decode, reverse-engineer, and document complex business logic embedded within legacy workflows and data pipelines, successfully converting and migrating them into new analytics tools and console frameworks.
• Independent Project Leadership: Lead analytics projects independently from conception to deployment, managing project timelines, production support, and the delivery of business-critical solutions.
• Process Automation & Tech Debt Reduction: Design, automate, and optimize analytics tools to better plan, predict, and monitor sample performance, significantly reducing tech debt associated with legacy architectures.
• Business Intelligence & Insights: Conduct research and quantitative analysis using descriptive, prescriptive, and statistical methods to deliver actionable insights and executive dashboards for business stakeholders.
• Cross-Functional Collaboration & Governance: Collaborate with cross-functional teams to align analytics workflows, implement data governance processes, and ensure timely issue resolution and production delivery.

Qualifications & Experience

• Education: Bachelor’s or Master’s degree in Statistics, Mathematics, Analytics, Data Science, Computer Science, or a related quantitative field.
• Experience: 5+ years of experience in quantitative analysis, data science, data analytics, or operations research.
• Statistical Mastery: Strong background in statistical modeling and testing procedures (e.g., A/B testing, ANOVA, Regression, Time Series, Correlation, and hypothesis testing).
• Technical & Migration Skills:
• 5+ years querying large relational databases using SQL (e.g., PostgreSQL, Oracle).
• 5+ years using scripting languages for data manipulation and statistical modeling (e.g., Python with SciPy, NumPy, and Pandas).
• 5+ years in data integration, analytics workflow conversion, and ETL tools (e.g., Alteryx, Databricks).
• 5+ years developing visualizations and executive dashboards using tools such as Tableau or BI platforms
• Communication & Leadership Competencies:
• Excellent verbal and written communication skills with a proven ability to explain complex statistical concepts to non-technical audiences concisely.
• Ability to lead projects independently, prioritize multiple assignments, and solve complex problems in time-critical environments.
• Strong attention to detail, commitment to data quality, and proactive drive for process improvement.

Optional Qualifications

• Experience with process improvement methodologies such as Lean or Six Sigma.
• Familiarity with Agile project management tools (Jira, Confluence, or Smartsheets).
• Alteryx Core Certification or experience working with cloud ecosystems (Databricks, AWS).

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