Senior Statistician 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.

Overview

This job description details the responsibilities and qualifications required for a Senior Statistician I. The role primarily focuses on statistical analysis to support research, modeling, and decision-making initiatives.The ideal candidate will have a strong background in developing and deploying advanced analytical models, a deep understanding of statistical methods, and expertise in scalable data processing within cloud environments. This role requires at least 5-10 years of professional experience in data science or a related quantitative field.

The Senior Statistician I role provides an opportunity to contribute to methodological innovation in the exciting and fast changing world of media measurement. This position will enhance existing methodologies and develop new ones to measure audiences across platforms. This is an ideal position to grow as a researcher, contribute to innovative products, and deploy cutting edge methodologies across platforms in audience measurement methodology.

In this role, you will work closely with other members of the team to optimize the current codebase, create simulation environments and pipelines, and have the opportunity to conduct research that will enhance the utility of our data. In addition, you will have the opportunity to grow your statistics and  data science skills through all aspects of the data science workflow and data product lifecycle. Responsibilities would range from methodology development, analysis, lightweight automation to designing and building robust/scalable code packages.

Responsibilities

• Statistical Research & Analysis: Design, execute, and interpret ANOVA (t-tests, multi-factor, repeated measures) and other parametric/non-parametric tests to test hypotheses, draw statistically sound conclusions, and inform business or scientific decisions. Apply rigorous statistical methods and experimental design to validate hypotheses, measure model performance, and provide data-driven recommendations

• Sampling Strategy & Design: Develop and implement effective sampling methodologies (e.g., random, stratified, cluster, systematic) to ensure data representativeness, minimize bias, and optimize resource allocation for data collection efforts. Calculate and justify appropriate sample sizes and power analysis.

• Data Preparation & Feature Engineering: Clean, preprocess, and transform complex datasets, applying statistical principles to feature selection and engineering to enhance model performance.

• Utilize and program in statistical software packages such as R, SAS, Python, and SQL to manage, analyze, and visualize data

• Manage code versioning and collaboration using GitLab. Document work, manage tasks, and track progress using Confluence and Jira

• Implement and monitor rigorous QA/QC protocols to ensure the accuracy, reliability, and integrity of data and analyses, often in compliance with regulatory guidelines

• Reporting & Communication: Communicate complex analytical results, statistical methods, and model performance metrics clearly and concisely to technical and non-technical stakeholders through reports, visualizations, and presentations.

• Collaboration & Mentorship: Collaborate with cross-functional teams (e.g., engineers, product managers, domain experts) to define research questions and implement data-driven solutions.

• Learn and become an expert in Digital Audience Measurement, with a focus on data structures, computations, and sampling/weighting. 

• Data Quality : Define and implement data quality assessments. Perform creative and effective analyses of input and output data. Create dashboards with informative data visualization

• Key tasks include – but are not limited to – sample weighting, data integration, examining large volumes of data, identifying and explaining trends and/or discrepancies, and identifying methodological and process improvements

Qualifications & Skills

• 5-10 years of professional experience as a statistician or in a related role.
• Bachelor's or Master's degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, or Engineering.
• Knowledge of data visualization tools (Tableau, Power BI) and database languages (SQL) is a plus.
• Strong analytical and problem-solving abilities, excellent written and verbal communication skills, attention to detail, and the ability to work both independently and as part of a collaborative team
• Collaborative code development experience, including version control, unit/integration testing, code review and sharing
• Ability to work alone and in a team
• Strong communication and presentation skills, with a keen eye for detail;
• Experience with taking the (technical) lead in projects; project management experience and working in an agile setting is a plus
• Experience with coaching junior colleagues is a plus

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