Data Scientist

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 leadership
• OR 1-2 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)

Key Responsibilities:

• 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).