Data Scientist

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**ABOUT THE ROLE**

Data Scientist role is responsible for providing statistical support for Television Audience Measurement including linear and nonlinear platforms.

The role is responsible for tailor made large scale survey design and the universe estimation from survey database, implements and improves sampling and weighting methodologies.

The Data Scientist independently implements and improves methodologies are applied for: data validation and quality control to ensure data quality standards are achieved as well as for maintaining viewing data integrity; identifying and resolving issues that may arise and specifying necessary corrective measures.

The Data Scientist independently analyses datasets, creates statistical models and presents the results for internal and external clients, supports the data communication with creative data visualization techniques. The Data Scientist also applies their experience to contribute insights for methodology and product enhancement of Nielsen linear and nonlinear TV measurement solutions.

The Data Scientist is open to learn and adopt new software to improve and automatize the procedures.

**CORE RESPONSIBILITY**

**Survey design, universe estimation**:

- Defines and controls the sampling and weighting methodology and design.
- Creates and improves questionnaire design.
- Controls the quality of survey database and enhances the routine of the data checks.
- Performs universe estimation
- Designs tests on new universes/weighting structures:To check the accuracy of the implementation.To check the impact on weighting results, weight distribution and weighing efficiency. To evaluate the effect at the viewing.To monitor coherence and consistency between the estimated universe and the productive sample

**Panel sample maintenance**:

- Contributes to delivery and improvement demo update and other surveys including questionnaire design and data collection approach.

**Data quality**:

- Recommends quality control and data validation improvement of linear and nonlinear viewing data
- Identifies any distortion on the data or low quality issue that might require further investigation and/or data reprocessing
- Monitors sample distribution and recommends strategies to correct any deviation.
- Performs analyses supporting data quality queries of the Client

**Viewing data and panel sample measurement analysis**:

- Performs regular reviews routine aspects of the service (e.g. as required from reviews to the panel controls, weighting, etc) and proposes adjustments and enhancements as required
- Produces complex trend analyses of linear and nonlinear viewing
- Performs viewing behavior analysis to detect any abnormality on the trends.
- Performs panel behavior analysis to detect any abnormality on the trends.
- Checks extreme viewers to verify the consistency of the behavioral trend.
- Implements multi-variable statistical models for deeper understanding of the data.

**Client communication**:

- Participates or presents in Client meetings as required.
- Contributes to the preparation of client-facing materials
- Creates regular and ad hoc reports and evolves them in line with Client requirements

**Product enhancement**:

- Proactively recommends product improvement elements

**Reports and documentation**:

- Produces the Reference Manual sections related to DSci responsibility.
- Produces quality control reports based on client requirements.
- Produces management reports as required.
- Provides analytical support and assistance to all areas of Nielsen DA when necessary.
- Prepares documentation of Data Science procedures and keeps them updated.

**Educational Background/Knowledge**:

- Level of studies: University Degree or Diploma
- Type of studies: statistics or sciences (mathematics) or sociology or economy
- 5 or more years Data Scientist work experience
- Work experience in the area of media research is preferred
- A solid understanding of statistical concepts and techniques used in a market research environment, including complex data approaches as fusion, complex data analyses and modeling techniques
- Computer literate using R or PythonWork experience with Machine Learning and Artificial Intelligence is advantage.
- Proficient in English

**Skills/Competencies**:

- Exceptional communication skills & Professional interaction: To maintain an excellent level of communication with external/internal collaborators
- Outstanding analytical and planning skills (Problem solving): To be able to identify a problem and to generate timely solutions