Lead Data Scientist

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.
Lead Data Scientist - Big Data in TV Measurement Including big data sources in the National TV ratings is a crucial component of Nielsen ONE, Nielsen’s long-term vision for a standardized single source of cross-platform content and ad measurement. The Big Data in TV Measurement initiative will expand Nielsen’s core audience measurement capabilities to encompass TV programs and ad exposures, including both linear ads and dynamically inserted ads that target specific audiences.
This work requires integrating data from addressable-capable data partners, such as smart TVs and digital cable and satellite providers, with Nielsen’s traditional panel measurement. We are currently looking for a Lead Data Scientist to support the development and implementation of foundational statistical methodologies to measure TV content and ad viewership from big data sources.

Responsibilities:

• Lead complex research projects from beginning to end -- direct project planning, develop innovative new methodologies, enhance existing methodologies, run simulations and analyses, etc.
• Supervise and collaborate with other Data Scientists to execute research and development tasks
• Support deployment and maintenance of data pipelines and models in a production environment
• Work with cross-functional teams to productionize, validate, and optimize methodologies
• Provide technical guidance and training for other team members
• Summarize, document, and communicate research findings to audiences of varying levels of subject matter expertise
• Stay abreast of developments in research methodology and changing technologies in the marketplace and proactively identify applications of these latest developments to improve existing methods

Qualifications:

• Masters degree in data science, statistics, mathematics, social sciences, biological and physical sciences, computer science, or engineering
• 4+ years research experience in a business setting
• Expertise in data analytics, statistics, and machine learning techniques
• Proficient in Python and and SQL (and/or PySpark and Spark SQL)
• Proficient with statistical and machine learning libraries (e.g., scikit learn, Spark MLlib)
• Well-versed with data visualization tools (e.g., Matplotlib, Plotly, Tableau)
• Experience with big data technologies (e.g., Spark, AWS)
• Software engineering experience, including version control (git), unit/integration testing, code review
• Excellent written and verbal communication skills
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