Job Description

ABOUT THIS JOB

You will be responsible for the research, design and development of advanced mathematical, machine learning and statistical algorithms, and for expanding our current analytical tools and capabilities.

RESPONSIBILITIES:

• Designing, validating and implementing new learning algorithms suitable for choice modeling and forecasting in-market performance of future products

• Developing and integrating machine learning pipelines to address core business problems and deliver insights

• Integrating different data sources at different levels of granularity in order to produce more accurate predictive models

• Designing stochastic simulations for testing and validating various models

• Improving the computational efficiency and scalability of various statistical models

• Developing, implementing and maintaining good programming standards and practices across our analytics codebase

• Keeping up with the state-of-the art in relevant areas – Machine Learning, Operations Research, Statistics, Artificial Intelligence, Marketing Science

A LITTLE BIT ABOUT YOU

If you are an enthusiastic individual who likes to work on a range of cutting-edge problems in a field that brings together human cognition, consumer behavior, statistical modeling, machine learning and software development,You will be part of a highly focused group of talented and creative engineers and scientists;Our work seeks to leverage Nielsen’s vast sales data assets in building the next generation of machine learning algorithms, to supplement our industry leading success prediction and volume forecasting models for new product launches;Our research and development efforts focus on developing new capabilities to meet the expanding scope of our business and our clients’ needs, as well as improving the performance and scalability of our current optimization and measurement platform.

QUALIFICATIONS 

• Masters or PhD in Computer Science, Engineering, Statistics, Mathematics, Operations Research, or other relevant scientific field

• 4+ years of experience with scripting languages, in particular R and Python

• Solid understanding of mathematical modeling, probability and statistics, and the design and simulation of stochastic systems

• Deep understanding of the mathematics behind the important elements of statistical learning algorithms such as Maximum Likelihood Estimation (MLE), Hierarchical Bayes (HB) Estimation, Hidden Markov Models (HMMs) and Markov Chain Monte-Carlo (MCMC)

• Firm knowledge of classical machine learning techniques such as random forests, SVMs, centroid-based and hierarchical clustering algorithms

• Hands-on experience with cutting-edge techniques in NLP and text mining, sentiment analysis and feature extraction

• Strong knowledge of Relational Databases and SQL programming

• Excellent communication skills and the ability to present complex ideas in a clear and concise manner to a variety of audiences

In addition to the above requirements, the following would be desirable:

• Familiarity with Discrete/Combinatorial Optimization techniques

• Experience with MongoDB

• Experience with Web Services and REST APIs

• Experience with Streamlit and R-Shiny

• 2+ years of object-oriented programming experience (Java and C# preferred)

Additional Information

ABOUT NIELSEN We’re in tune with what the world is watching, buying, and everything in between. If you can think of it, we’re measuring it. We 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 our clients. Today’s data is tomorrow’s marketplace revelation.

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

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