Data Scientist

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming

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 Data Scientist, you’ll be part of a team of smart, highly skilled Global Data Scientists who enhance our products to remain relevant in the changing environment and enable clients to use our data effectively. This position requires someone who is passionate about learning, consumer-sourced data, data quality, statistical measurement, automation, efficiency, and consumer behavior.

What you’ll do

• Support the development of new products. The primary areas include – but are not limited to – trend analysis, identifying gaps in coverage, representation/ sampling, bias reduction, indirect estimation, data integration, automation, generalization, and harmonization

• Identify, develop and make recommendations for process improvements and best practices; own implementation of recommendations required.

• Help solve client challenges (e.g. performance mgmt., product or methodology evolution POC). Translate Clients’ requirements into actionable solutions or products.

• Interpret, document, and present/communicate analytical results to multiple business disciplines and stakeholders, providing conclusions and recommendations based on customer-centric data. Be an internal expert in advanced capabilities.

We’re looking for people who have

• Proficiency in Python (or R), SQL or other statistical packages, bitbucket

• Previous experience with Panel Data and/or data interpretation in a research context.

• Knowledge of data projection techniques, the theory of estimation, and modeling methodologies ( regression, Classification, some Machine Learning)

• Excellent communication, data visualization & presentation skills, with the ability to effectively interface across cross-functional technology teams and the business

• Minimum B.S. degree in Statistics, Data Science, Actuarial Sciences, Operations Research, Econometrics, or a similar quantitative field.