North America / United States / PA / Pittsburgh
#: 84923-en_US / 84923
Lead Data Scientist – 84923
Data Science – USA Pittsburgh, Pennsylvania
The Identity / Cross-Functional Development team develops and implements products that measure and predict audience for various types of content and ad campaigns across TV and Digital platforms. We are looking for a Lead Data Scientist to contribute to R & D initiatives across the team. Responsibilities include developing and enhancing methodologies to estimate audience (and its demographic composition) for specific programs, taking a lead on the implementation of these methodologies, and identifying areas of future development. While working on these methodologies, emphasis should be placed on automation, scalability, and object-oriented coding that can be leveraged to build various products relying on the metrics already available within Nielsen.
What will I do?
- Utilize and develop innovative machine learning / deep learning methodologies to improve audience estimates based on large volumes of data from various sources
- Make decisions on the selection of methodologies, technical tools, and processes that most effectively and efficiently reach the desired outcome
- Work with Agile, cross-functional scrum teams to productionalize, validate, and optimize methodologies
- Support deployment and maintenance of data pipelines and models in a production environment
- Develop and implement strategies to automate production of methodologies
- Stay abreast of developments in quantitative research methodology and changing technologies in the marketplace and proactively identify applications of these latest developments to improve existing methods
- Provide support for technical guidance and training of other team members
- Summarize, document, and communicate research findings to audiences of varying levels of technical subject matter expertise
Is this for me?
- Master’s degree in data science, statistics, mathematics, social sciences, biological/physical sciences, computer science, or some other quantitative research field
- At least 3 years research experience in a business setting
- Outstanding statistical and analytical skills with expertise in machine/ deep- learning techniques
- Proficiency in Python
- Experience with modern machine learning libraries and frameworks (e.g. LightGBM, XGBoost, PyTorch, TensorFlow, Stan, etc.)
- Experience with cloud environments and big data technologies (e.g., Spark, AWS)
- Collaborative code development experience, including version control, unit/integration testing, code review and sharing (preferably in Git)
- Knowledge of Bayesian inference and probabilistic programming (e.g. Pyro)
- Knowledge of Natural Language Processing
- Skilled at feature engineering
- Subject matter intuition for the causal drivers of media consumption
- Knowledge of data visualization tools/packages
- Some experience working within Agile teams
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: Pittsburgh,Pennsylvania
Secondary Locations: , , ,