Sr. Data Scientist

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.

Job Summary

The Big Data and Panel Integration team within the Data Science organization focuses on improving and enhancing Nielsen’s highly successful audience measurement products out in the marketplace for advertising and content measurement. As part of this exciting team, this position will focus on developing new methodologies to measure audiences across platforms (including on “connected” or “over the top” devices, smart TVs, or set top boxes) and on evaluating and integrating new data assets and partners into Nielsen’s existing methodologies in order to enhance or expand the data delivered to clients. 

The Senior Data Scientist role provides an opportunity to contribute to methodological innovation in the exciting and fast changing world of media measurement. This position will develop new methodologies to measure audiences across platforms and integrate new big data data assets into Nielsen’s existing methodologies. 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 and maintain the current codebase, create simulation environments and pipelines, and have the opportunity to conduct research that will enhance the utility of our data. You will also write new coding packages to support the refinement processes of behavioral media tuning data (e.g. household demographic assignment, big data editing rules, big data refinement models) by producing production ready code (scalable, reusable/modular). In addition, you will have the opportunity to grow your data science skills (coding, statistics) through all aspects of the data science workflow and data product lifecycle. Responsibilities would range from methodology development, analysis, lightweight automation to designing, building, and maintaining robust/scalable code packages.

Responsibilities

• Own reproducible data science projects end-to-end.
• Deploy and maintain data pipelines and models in a production environment.
• Work with cross-functional teams to productionize, validate, maintain, and optimize methodologies.
• Conduct research and analytics to ensure methodologies are fit for purpose and working as intended; troubleshoot, diagnose, and resolve when they are not.
• Provide technical mentorship.
• Communicate research findings to varying audiences.
• Develop, implement and maintain good programming standards and practices across our data science and analytics codebases.
• Champion and govern best practices for data use and software development.
• Use git and cloud development tools extensively to iterate and improve data science workstreams.

Qualifications

• Bachelor’s or Master’s (preferred) degree in a quantitative research field, such as computer science, data science, statistics, 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)
• Excellent verbal and written communication skills.
• Excellent software engineering fundamentals.
• Excellent debugging skills.
• Excellent machine learning fundamentals.
• Outstanding statistical and analytical skills.
• Collaborative code development experience, including version control, unit/integration testing, code review and sharing.
• Curiosity and skepticism

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