Research Analyst

NielsenIQ BASES is a forward-thinking, rapidly growing, market research division of the NielsenIQ Company. That means we maintain an unbeatable client list, create best-in-class solutions, and have access to incredible resources—without sacrificing the benefits of a smaller, leaner, close-knit company. We celebrate curiosity and creativity and encourage openness and collaboration.

We’re highly driven, team-oriented, and psyched to use cutting-edge technologies to change how the world’s leading consumer companies innovate.

Through innovative market research technologies (such as evolutionary optimization, specialized choice modeling, and neuroscience) and client consulting, we help major consumer product companies dramatically identify breakthrough product ideas, messaging that inspires action, fresh package designs, and optimal launch strategies.

At BASES, we work in a field that combines consumer behavior, human cognition, statistical modeling, machine learning, and software development. Our work seeks to combine NielsenIQ’s vast household and POS data assets with our industry-leading consumer research methods, to help our clients succeed with their innovations and new product launches. Our research efforts focus on developing more accurate and more scalable success prediction and volumetric forecasting models, to support the expanding scope of our business and our clients’ needs.

As a Research Analyst, you would be responsible for executing various data modeling & statistical analyses for Global clients. You would also contribute significantly to various research and developmental initiatives & automating processes. These may range from consumer choice and decision-making models to volumetric forecasting models, marketing mix models, and assortment and pricing optimization algorithms.

What you'll do

● Developing statistical and machine learning models to predict consumer behavior, discrete choice, integrating survey, household, and retail sales data

● Validating and calibrating current learning algorithms to estimate the success likelihood and volume potential of future products

● Developing models for estimating the impact of various advertising and marketing activities on sales.

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

Requirements

Master’s degree (2 years full time) or higher in Statistics, Mathematics, Data Science, or Computer Science, Operations Research, with a high level of academic achievements

● Strong expertise in R-programming and Python knowledge.

● 0-1+ years of experience with scripting languages, particularly in Python and R.

● Solid understanding of mathematical & statistical modeling (preferably a good understanding of various statistical techniques like probability theory, Bayesian inference, Maximum Likelihood Estimation (MLE), Hierarchical Regression Models, Mixture Models, and Markov Chain Monte-Carlo (MCMC) sampling. etc.)

● Excellent communication skills and the ability to present complex ideas clearly and concisely to a variety of audiences.

Bonus points for those who have (Preferable)

● Possess object-oriented programming experience (Java and C# preferred),

● Experience with relational databases and SQL programming