Sr Data Scientist

United States

Full Time Senior-level / Expert USD 68K - 135K *
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A global leader in audience insights, data and analytics, Nielsen shapes the future of media with accurate measurement of what people listen to and watch.

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Our business is centered on data, because it’s what our clients need to make confident decisions that shape the future of media. Our Data Science team delivers essential metrics and insights to brands around the world through new product ideation, experimental design and complex analysis.
What is the role?Our Data Science team is experimenting, testing, and driving major insights that impact both a global network of clients and Nielsen’s direction. Excited? Come join us!The Cross Functional Development team builds and maintains mathematical, statistical, and machine learning models that measure cross-platform consumption of content and ads among different demographic groups. We ideate, test, implement, explain, and enhance these models to ensure that our measurements are the most accurate and comprehensive in the rapidly changing media landscape.
Who am I working with? / Why is this team cool?If you are passionate about clients, hungry to learn and want to drive change, join NielsenMedia’s Data Science team! Our Data Scientists use their deep understanding of the business context, evolving client needs, underlying data, and their data science skills to apply the latest methodologies and technologies to innovate across Nielsen’s product portfolio.
Why do I want to work here?As the arbiter of truth, Nielsen Global Media fuels the media industry with unbiased, reliable data about what people watch and listen to. To discover what’s true, we measure across all channels and platforms⁠—from podcasts to streaming TV to social media. And when companies and advertisers are armed with the truth, they have a deeper understanding of their audiences and can accelerate growth.

What will I do?

  • Leverage machine learning and predictive models to develop and enhance digital measurement
  • Independently develop custom production-level Python and SQL code on Nielsen’s proprietary platform
  • Use git and cloud development tools extensively to iterate and improve data science workstreams
  • Identify gaps in data capture or data quality, and surface the value attached to filling those gaps.
  • Collaborate with our software engineers and product leaders to integrate and test new or updated modules in production pipelines
  • Enhance and evolve existing solutions to meet changing business needs with agility.
  • Perform deep dive analyses on key modeling insights from different perspectives and package the insights into easily consumable presentations and documents
  • Represent Data Science in discussions with relevant stakeholders (provide relevant information, convey findings and concerts, etc.)

Is this for me?

  • Data Scientist with a degree in a quantitative field like mathematics, statistics, computer science, engineering, machine learning, econometrics, etc.
  • 3+ years of experience with the following:
  • Building and maintaining Machine Learning or Deep Learning methodologies
  • Intermediate coding in Python and SQL
  • Experience with machine learning libraries and frameworks (e.g. LightGBM, XGBoost, PyTorch, TensorFlow, etc.)
  • Contribution to production code and pipeline development
  • Working in cloud-based environments, ideally AWS
  • Use of git/code versioning and code reviews

Also nice to have:

  • Great communication skills
  • Expertise working in cross-functional teams
  • Familiarity with digital media measurement
  • Some knowledge of graph theory and / or Bayesian inference

* Salary range is an estimate based on our salary survey at

Tags: AWS Bayesian Computer Science Deep Learning Econometrics Engineering Git LightGBM Machine Learning Mathematics Pipelines Python PyTorch SQL Statistics Streaming TensorFlow Testing XGBoost

Perks/benefits: Career development

Regions: Remote/Anywhere North America
Country: United States
Job stats:  8  2  0
Category: Data Science Jobs
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