North America / United States / MA / Needham /

Data Science

#: 743999734890132 / 50241490

Mid-Senior Level


Job Description

Our Data Science teams help to provide NielsenIQ’s clients with the most complete understanding of the market and its consumers. With a footprint in over 100 countries across the globe, our expansive data and measurement capabilities provide market context and confidence. We are constantly innovating to keep pace with emerging market trends and the increasingly diverse, demanding, and connected consumer.

As a Lead Data Scientist, 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.

What you’ll do

  • 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

We’re looking for people who have

  • 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)