At Nielsen, we believe that career growth is a partnership. You ultimately own, fuel and set the journey. By joining our team of nearly 14,000 associates, you will become part of a community that will help you to succeed. We champion you because when you succeed, we do too. Embark on a new initiative, explore a fresh approach, and take license to think big, so we can all continuously improve. We enable your best to power our future. 
Aim of the position
The Senior Data Scientist position will support the statistical operations and methodological enhancement of our Television Audience Measurement product portfolio, using the right data, algorithms, and tools to ensure Nielsen clients receive a complete and representative view of how people watch media content. Make an immediate impact as we evolve our methodologies to fuel Nielsen’s overall strategy of transforming audience measurement, blending the strengths of high quality representative panel data with the scale of “big data” assets such as set top boxes and smart TVs.
In this role, you will have the opportunity to grow your foundational data science skills (coding, statistical research, and analytics) through all aspects of the data science workflow and data product lifecycle. You will support the research and development of statistical and methodological processes (e.g. sample weighting, data integration, audience estimation) by producing scalable, reusable/modular code that facilitates reproducible research. You will work closely with other members of the team to optimize the current codebase, create simulation environments and have the opportunity to conduct research & analytics on topics that will enhance the utility of our data (project areas will include such topics as representation/sampling, bias reduction, trend analysis, indirect estimation, and predictive modeling.).
The ideal candidate will have a strong desire to understand all aspects of Nielsen data, grow their technical and statistical skills to facilitate reproducible research and analytics, and to understand our clients’ problems to ensure our data methodologies directly address and solve them

Responsibilities

• Learn and become an expert in US TV Audience Measurement, with a focus on data structures, computations, and sampling/weighting.
• Conduct research and analytics to ensure methodologies are fit for purpose and working as intended; troubleshoot, diagnose, and resolve when they are not.
• Independently write custom Python and SQL code.
• Develop, implement and maintain good programming standards and practices across our data science and analytics codebase.
• Champion and govern best practices for data use and software development.
• Use git and cloud development tools extensively to iterate and improve data science workflows
• Implement strategies to automate implementation of methodologies, inclusive of DQA to identify potential quality escapes. Actively participate in code reviews.
• Support analyses for Data Science teams including custom requests, client inquiries, impact of changing methodologies, standards and best practices.
• Proactively gather information, as needed, to work independently as well as in a team environment.
• Key tasks include – but are not limited to – data integration, automation, examining large volumes of data, identifying trends and/or discrepancies, and identifying methodological and process improvements.

Skills (Which qualifications, skills are necessary for this role)

• Bachelor’s or Master’s (preferred) degree in a quantitative research field, such as data science, statistics, survey research, mathematics, biological/physical sciences, etc.
• 3-5 years code development/research experience in a business setting
• Strong proficiency with Python, Spark, SQL, Unix, git, and AWS (S3 and EC2)
• Collaborative code development experience, including version control, unit/integration testing, code review and sharing
• Excellent problem solving and critical thinking skills
• Excellent verbal and written communication skills
• Excellent coding fundamentals
• Excellent troubleshooting and debugging skills
• Outstanding statistical and analytical skills
• Curiosity and skepticism