At Nielsen, we believe that career growth is a partnership. You ultimately own, fuel and set the journey. By joining our team of nearly 14,000 associates, you will become part of a community that will help you to succeed. We champion you because when you succeed, we do too. Embark on a new initiative, explore a fresh approach, and take license to think big, so we can all continuously improve. We enable your best to power our future.
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 Nielsen Marketing Cloud 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.The Nielsen Marketing Cloud 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.
Skills Required:
- 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 leadership3-5 years of work experience focusing on the following:Creating, organizing, analyzing, and correcting very large datasets using statistical modelsCoding 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 stakeholdersExcellent communication & presentation skills (written and verbal)Experience in media or marketing analytics, e.g. lookalike modeling, insights analysis, customer segmentationAbility to work independently and solve complex problemsNaturally curious, has a passion for solving problems and critical thinkingGood 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 AWSWorking 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)
Key Responsibilities
- Build, evaluate, and maintain propensity models at scaleWrite 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 NMC 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 fieldConfidently represent Data Science methods and approaches to internal and external partners and clients.
- Participate in internal and external knowledge exchanges (conferences, workshops, webinars).