North America / United States / NY / New York City

Data Science

#: 84909-en_US / 84909

Regular

Full-Time

Data Scientist – Identity Team – 84909

Data Science – USA New York, New York 

 

What is the role?

Nielsen is the largest measurement company in the world with unique measurement technologies, assets, and data that make it one of the most interesting and challenging places for a data scientist to work.  We focus on what consumers watch, listen to, and buy in over 95 countries.
 
Data Science is core to what Nielsen does, and our research projects have high visibility in directly affecting the results of our business and our clients.   This Senior Data Scientist role in the Media Identity team provides an opportunity to contribute to methodological innovation in the exciting and fast-changing world of digital media measurement. This is an ideal position to grow as a model builder, developer, researcher, and to contribute to innovative products.

What will I do?

  • Build, evaluate, and maintain propensity models at scale
  • Write production level code that integrates seamlessly into already productized model building pipeline
  • Develop and implement new machine learning techniques to improve performance of client facing models in production
  • Automate model surveillance and maintenance in order to streamline modeling system
  • Research and develop new use cases for Nielsen Identity data assets
  • Support the business and client teams by investigating complex analytical challenges
  • Stay up to date on industry changes to digital measurement (e.g., new devices and platforms, privacy laws updates, changes in browser/app measurement, etc.) and critically assess how it would impact Nielsen measurement.
  • Engage in discussions on strategic direction of product from a client perspective.
  • Stay informed of new research and developments in the field
  • Confidently represent Data Science methods and approaches to internal and external partners and clients.
  • Participate in internal and external knowledge exchanges (conferences, workshops, webinars).

Is this for me?

This position requires a detail-oriented person who has experience in big data analysis using multiple data sources and statistical research, and who enjoys working in a fast-paced environment.

  •  Ability to problem-solve, work independently on critical initiatives and see the big picture are keys to success in this position.
  • Master’s in statistics, quantitative social sciences, economics, operations research, or hard sciences (e.g. engineering, computer science, biology, physics, etc.) with outstanding analytical expertise and strong technical leadership
  • OR 3-5 years of work experience focusing on the following:
  • Creating, organizing, analyzing, and correcting very large datasets using statistical models
  • Coding in data science-related programming languages; required experience with Python (numpy, pandas, sci-kit learn, etc.)
  • Proficiency in SQL & big data technologies.
  • Leading and managing complex projects with multiple stakeholders
  • Excellent communication & presentation skills (written and verbal)
  • Experience in media or marketing analytics, e.g. lookalike modeling, insights analysis, customer segmentation
  • Ability to work independently and solve complex problems
  • Naturally curious, has a passion for solving problems and critical thinking
  • Good vibes, integrity, and good work ethic

 

Skills Desired:

  • Experience with online media and the ad tech ecosystem
  • Experience working with global cross-functional teams of various sizes
  • Experience with machine learning techniques
  • Experience working with cloud-based computing and storage solutions, preferably AWS
  • Working knowledge of Bash and Git
  • Experience with other tools common to the data science world such as Airflow, Spark, MLlib, MLflow, Tensorflow, and PyTorch
  • Experience with data visualization tools (e.g. Superset)

Who am I working with?

The Identity team within the Data Science Global Media organization focuses on creating a holistic view of individuals and households across all channels and devices, unifying online browsing behaviors, offline panel data, mobile device usage, as well as linear and digital television viewership. Using our expertise in big data, analytics, and machine learning, we enable marketers to engage individuals and households with personalized messaging, drive performance at scale, and holistically measure marketing effectiveness. As part of this exciting team, this position will focus on developing new methodologies, data mining and predictive modeling, and the automation of our modeling processes.

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ABOUT NIELSEN

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. 

Do you want to move the industry forward with Nielsen? Our people are the driving force. Your thoughts, ideas and expertise can propel us forward. Whether you have fresh thinking around maximizing a new technology or you see a gap in the market, we are here to listen and take action. Our team is made strong by a diversity of thoughts, experiences, skills, and backgrounds. You’ll enjoy working with smart, fun, curious colleagues, who are passionate about their work. Come be part of a team that motivates you to do your best work!  

Nielsen is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class.

Job Type: Regular 

Primary Location:  New York,New York 

Secondary Locations: IL – Chicago, Remote, , 

Travel:  No