Principal Data Scientist (Remote)
United States
Nielsen
A global leader in audience insights, data and analytics, Nielsen shapes the future of media with accurate measurement of what people listen to and watch.Principal Data Scientist
Data Science is at the core of Nielsen’s business. Our team of researchers come from diverse disciplines and they drive innovation, new product ideation, experimental design and testing, complex analysis and delivery of data insights around the world. We support all International Media clients and are located where our clients are.
By connecting clients to audiences, we fuel the media industry with the most accurate understanding of what people listen to and watch, and how this engagement affects their choices from media and brand engagement to purchase. As the world’s largest research organization, Nielsen is powered by talented, creative scientists and researchers. Our Audience Outcomes Data Science associates come from diverse disciplines that include business, statistics, economics, engineering, mathematics, operations research and physics. These professionals drive innovation by continually improving complex analyses that deliver valuable insights to our clients. Because measurement is at the core of our business, our products have high visibility and make a direct impact on our clients.
Our team has an opportunity available for a Principal Data Scientist. The ideal candidate must have work experience in the development of econometric models, expertise in modern analytics programming, 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
- Research, design, develop, implement and test econometric, statistical, causal inference and machine learning models.
- Create various prototypes for research and development purposes.
- Design, write and test modules for Nielsen analytics platforms using Python, R, SQL or Spark.
- Utilize advanced computational/statistics libraries including Spark MLlib, Scikit-learn, SciPy, StatsModels or R.
- Documents and presents econometric, statistical and causal inference methods to within company associates.
- Partners with Product organization on resolving data issues.
- Work with Product on setting the direction for new analytics research and product development for engaged track(s)
Requirements
- Graduate degree in Statistics, Economics, Applied Mathematics, Computer Science, Engineering or other Quantitative field of study.
- 5+ years of work experience in delivering analytics software solutions in a production environment.
- 5+ years of 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 coding and testing of analytical modules using Python, SQL and Spark.
- Expertise in at least one statistical software package, such as R or StatsModels.
- Experience with Git or other version control tools.
- Well-organized and capable of handling multiple mission-critical projects simultaneously while meeting deadlines.
- Exceptional problem solving skills.
- Excellent oral and written communication skills.
- Critical thinking skills to evaluate results in order to make decisions.
- Abilities to solve problems independently and within a team.
- Work with cross-functional team to resolve any hurdles in the projects.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Causal inference Computer Science Economics Engineering Git Machine Learning Mathematics ML models Physics Python R Research Scikit-learn SciPy Spark SQL Statistics statsmodels Testing
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