Lead Data Scientist – Digital Innovation

  • 170 William St # 288
  • Full-time

Company Description

Nielsen

Job Description

Lead Data Scientist - Digital Innovation - 107196

Data Science - USA New York, New York 

 

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 Digital Innovation team builds and maintains mathematical, statistical, and machine learning models that measure the content and ads people interact with online.  We ideate, test, implement, explain, and enhance these models to ensure that our measurements are the best in the rapidly changing digital landscape.

 

What will I do?

  • Engineer predictive features for use in our current data modeling pipelines
  • Independently develop custom Python and SQL code
  • Provide research support that leads to the enhancement of existing methodologies or the creation of new methodologies
  • Use git and cloud development tools extensively to iterate and improve data science workstreams
  • Write well documented production level Python scripts and participate in code reviews
  • Collaborate with our software engineers and product leaders as you integrate and test new or updated modules in production pipelines
  • Create and manage multiple projects from beginning to end including analysis design, execution, summarization, and communication of results
  • Regularly mentor and teach junior associates
  • Serve as primary Data Science contact, initiate methodology discussions with relevant stakeholders, and provide final Data Science decisions
  • Serve as subject matter expertise for certain methodologies

 

Is this for me?

  • Data Scientist with a degree in mathematics, statistics, computer science, engineering, machine learning, or related field and 5+ years of experience with the following:
  • Building and maintaining Machine Learning or Deep Learning based methodologies
  • Advanced coding in Python
  • Advanced coding in SQL
  • Contributor to production code processes in our open source-based pipeline platform
  • Working in cloud-based environments, ideally AWS
  • Use of git/code versioning and code reviews

 

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 Nielsen Media’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.

 

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ABOUT NIELSEN

By connecting clients to audiences, we fuel the media industry with the most accurate understanding of what people listen to and watch. To discover what audiences love, we measure across all channels and platforms⁠—from podcasts to streaming TV to social media. And when companies and advertisers are truly connected to their audiences, they can see the most important opportunities and 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: Remote, , , 

Travel:  No