At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future. Responsibilities Use and fit different mathematical and econometric models for explanatory purposes that deliver better decisions, and create high-quality data visualizations for internal and external purposes. Research, design and implement analytic and mathematical approaches and algorithms to build scalable best of class web-based analytical solutions Design and test analytical modules for Nielsen modeling platforms. Partner with our Software Engineering department to build best-of-class web-based analytical solutions. Document and present methodology inside and outside the company. Design and prioritize work for smaller teams Mentor newly hired associates Requirements PhD or Masters degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or Related field 4+ years experience in working in Data Science and/or Statistical analysis, Expertise in Python, Spark, SQL or other modern programming languages Experience in using machine learning libraries and techniques. Proficient in writing production grade code using scientific computing packages (e.g., NumPy, SciPy, Scikit-learn)Experience with Bayesian and Frequentist statistics Experience with cloud providers (e.g. AWS, Azure)Experience in code management, docker, and CI/CD pipelines. Experience with Num Pyro is a plus. Well-organized and capable of leading multiple mission-critical projects simultaneously while meeting deadlines Excellent oral and written communication skills Attention to detail – quality, and accuracy in all work and interactions Quick learner with a logical mindset and analytical thinking who is passionate about technology Experience in short-release life-cycle (agile processes including scrum)
Responsibilities
Use and fit different mathematical and econometric models for explanatory purposes that deliver better decisions, and create high-quality data visualizations for internal and external purposes.
Research, design and implement analytic and mathematical approaches and algorithms to build scalable best of class web-based analytical solutions
Design and test analytical modules for Nielsen modeling platforms
Partner with our Software Engineering department to build best-of-class web-based analytical solutions
Document and present methodology inside and outside the company
Design and prioritize work for smaller teams
Mentor newly hired associates
Requirements
PhD or Masters degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or Related field
4+ yrs experience in working in Data Science and/or Statistical analysis
Expertise in Python, Spark, SQL or other modern programming languages
Experience in using machine learning libraries and techniques
Proficient in writing production grade code using scientific computing packages (e.g., NumPy, SciPy, Scikit-learn)
Experience with Bayesian and Frequentist statistics
Experience with cloud providers (e.g. AWS, Azure)
Experience in code management, docker, and CI/CD pipelines
Experience with NumPyro is a plus
Well-organized and capable of leading multiple mission-critical projects simultaneously while meeting deadlines
Excellent oral and written communication skillsAttention to detail – quality, and accuracy in all work and interactions
Quick learner with a logical mindset and analytical thinking who is passionate about technology
Experience in short-release life-cycle (agile processes including scrum)
