Data Scientist – Global Research & Analytic Development 1205 views

Data Science – USA Needham, Massachusetts

At Nielsen they understand the importance of knowing what consumers Watch and Buy. As the world’s largest research organization, Nielsen is powered by talented, creative scientists and researchers. Their Research & Analytic Development associates come from diverse disciplines that include business, economics, engineering, mathematics, operations research, physics, and statistics. These professionals drive innovation and insight through continual ideation, complex analyses, and delivery of insights to their clients. Because measurement is at the core of Nielsen’s business, their products have high visibility and make a direct impact on their clients.

Their team in the Greater Boston Area has an opportunity available for a Data Scientist. The ideal candidate has work experience in the development of econometric models, expertise in modern analytics programming, tested and deployed machine learning and artificial intelligence techniques, the capacity to work in an agile development environment alongside software engineers, and a solid foundation in developing solutions for marketing, pricing and/or advertising organizations.

Responsibilities

• • Design econometric models, and supervised and unsupervised learning approaches
  • Create various prototypes for research and development purposes
  • Design and write modules for Nielsen analytics platforms using Python, R, Spark MLlib and Scala
  • Extract data using SQL
  • Document and present methodology inside and outside the company
  • Partner with our Software Engineering department to build best-of-class cloud-based analytical solutions

Requirements

• • Graduate degree in Statistics, Economics, Applied Mathematics, Computer Science, Engineering, or other Quantitative Field of Study
  • 2+ years work experience in delivering analytics software solutions in a production environment
  • 2+ years work experience in quantitative marketing analysis, with an emphasis on statistical, econometric and predictive analytic research that drives analytic product Innovation and implementation
  • Expertise in analytics programming languages such as Python (with pandas) and R
  • Solid understanding of mathematical modeling, probability and statistics, and the design and simulation of stochastic systems
  • Firm knowledge of classical machine learning algorithms such as regression, random forest, SVM and the mathematics behind them
  • Familiarity with optimization techniques and solvers
  • Familiarity with causal inference methods such as structural equation modeling
  • Exceptional problem solving skills
  • Well-organized and capable of handling multiple mission-critical projects simultaneously while meeting deadlines
  • Excellent oral and written communication skills

Desired

• • Experience with household/person-level loyalty card analytics
  • Experience in marketing mix modeling with Nielsen or IRI syndicated data
  • Experience with big data analytics and/or machine learning techniques, including Apache Spark
  • Experience with Scala
  • Short-release life-cycle experience (agile processes including scrum)

About Nielsen

They’re in tune with what the world is watching, buying, and everything in between. If you can think of it, they’re measuring it. They sift through the small stuff and piece together big pictures to provide a comprehensive understanding of what’s happening now and what’s coming next for their clients. Today’s data is tomorrow’s marketplace revelation.

They like to be in the middle of the action. That’s why you can find them at work in over 100 countries. From global industry leaders to small businesses, consumer goods to media companies, they work with them all. They’re bringing in data 24/7 and the possibilities are endless. See what’s next with them at Nielsen: careers.nielsen.com

Nielsen is committed to hiring and retaining a diverse workforce. They 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.