• United States Of America, Usa

Job Description:

The Lead Data Scientist is responsible for supporting all analytical needs for the Audience Measurement organization within Data Science

Job Responsibilities

Delivers all analyses to support KPI definition/ implementation, standards and best practices
Conducts analyses to support Methods programs
Leads prototyping (what ifs) as well as supporting pilot programs for R&D purposes The primary areas includes but not limited to trend analyses, 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
Address major quality escapes
Ensures documentation of the new methodologies and best practices
Work with cross-functional teams to design, implement, and test new consumer and audience measurement methodologies
Assist in the design and testing of data collection methodologies for Nielsen panels and surveys
Provide research support for the identification and implementation of methods and best practices to improve respondent cooperation and optimize data collection approaches
Represents Nielsen within academic and research councils

Role Requirements E=essential, P=preferred

E- Research Scientist -University Graduate with some relevant work experience

E- Sr Research Scientist 3 years of experience in market research

E- Bachelors degree in Statistics, Social Science, Operation Research, or other sciences (eg Engineering, Computer Science, Information Systems, Biology, Physics etc) with outstanding analytical expertise and strong technical leadership

E- Experience in trend analyses, multivariate statistics (parametric/ non-parametric), representation/ sampling, bias reduction, indirect estimation, data aggregation techniques, automation, generalization

E- Proficient in Python, R, Spark, Julia or comparable computing languages and frameworks

E- Proficient in building modular solutions that implement regression, classification, and dimensionality reduction

E- Knowledge of SQL and application of algorithms to large-scale datasets

P- Proficiency in pandas, numpy, scipy, scikit-learn, tensorflow, or equivalent packages

P- Proficient with algorithms and model building in a continuous integration/continuous deployment environment and large-scale databases

P- Advanced degree in Statistics, Social Science, Operation Research, or other sciences (eg Engineering, Computer Science, Information Systems, Biology, Physics etc)

P- Demonstrated experience in Nielsen methodologies, data collection, platforms, research processes and operations

P- Domain expert in at least one area Demography, Sampling, Statistics Modeling, Research Practices, Data Integration and/or Digital



Were in tune with what the world is watching, buying, and everything in between If you can think of it, were measuring it We sift through the small stuff and piece together big pictures to provide a comprehensive understanding of whats happening now and whats coming next for our clients Todays data is tomorrows marketplace revelation

We like to be in the middle of the action Thats 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 Were bringing in data 24/7 and the possibilities are endless See whats next with us at Nielsen careersnielsencom

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

Profile Summary:

Employment Type : Full Time
Eligibility : Any Graduate
Industry : Research/Surveyor/MR
Functional Area : IT Software : Software Products & Services
Role : Software Engineer
Salary : As per Industry Standards
Deadline : 12th Aug 2020

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