Sr Data Scientist

Key Skills

Java Programming, Python Programming, SQL, PowerBI, R Programming, Spotfire

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 Senior Data Scientist, you’ll be part of a Data Science Methods team that work on developing new innovative methodologies or enhancing the methodologies for data collection & estimation to bring efficiencies and create new opportunities.

Job Description

• Work with direct manager, colleagues, and other stakeholders such as Program team, Product Leaders, and others.
• Provide research support for the identification and implementation of methods and best practices to improve and optimize data collection approaches.
• Support implementation/deployment of methods/standards with other groups in countries
• Play a key role in developing and documenting new methodologies
• Lead and support analyses for the Methods group, including product analyses, client inquiries, impact of changing methodologies, standards, and best practices.
• Participate in data experiments and PoCs, setting measurable goals, timelines and reproducible outcomes. Apply critical thinking and take initiative
• Assist in prototyping (what –ifs) and support pilot programs for R&D purposes. These include trend analysis, identifying gaps for improvements in coverage, representation/ sampling, bias reduction, indirect estimation, data integration, automation, generalization, harmonization as well as working with different data sources.

Qualifications

• More than 4 years of work experience
• Good engagement/interaction/communication skills with different teams/stakeholders in the company (experts from other areas)
• Masters/PhD degree in Mathematics, Statistics, Data Science, Actuarial Sciences, Operations Research, or Econometrics
• Proficient in high-level programming languages (i.e. Python, R, SQL), as well as with data visualization tools (e.g. Power BI, Spotfire). Familiar with git/Bitbucket processes. 
• Experience in several of the following areas: machine learning, trend analysis, multivariate statistics (parametric/ non-parametric), sampling, data aggregation techniques, automation, generalization, and model validation techniques.
• Domain expert in at least one area: Demography, Sampling, Statistical Modeling, Research Practices, Data Integration, Digital.
• Ability to manipulate, analyze and interpret large data sources.
• Identify and use data from various sources to influence decisions.
• Effectively Interpret the data in relation to business objectives.