Senior Data Scientist_M

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).