At Nielsen, we believe that career growth is a partnership. You ultimately own, fuel and set the journey. By joining our team of nearly 14,000 associates, you will become part of a community that will help you to succeed. We champion you because when you succeed, we do too. Embark on a new initiative, explore a fresh approach, and take license to think big, so we can all continuously improve. We enable your best to power our future.
About the Role
You enjoy bridging the fields of data science, software development, and data engineering. You’re equally excited about building models at scale and writing production-ready software that can run in the cloud. You understand machine learning and know how to implement best software development practices across a team. You’re intellectually curious and prepared to learn from your peers.
Responsibilities
Build measurement and planning solutions for publishers, advertisers, and agencies.
Support reproducible data science projects end-to-end.
Deploy and maintain data pipelines and models in a production environment.
Work with cross-functional teams to productionize, validate, and optimize methodologies.
Communicate methodology and research findings to varying audiences.
Support research on methodology changes to cross-platform audience measurement. The primary research areas include trend analyses, imputing missing data, representation/ sampling, bias reduction, indirect estimation, data integration, and automation.
Continuous support and development of new projects by exploring the data - Variable Identification, cleaning the data , applying dimension reduction techniques, calculating distances and integrating the surveys. And also using output evaluation techniques in order to make sure of the accuracy.
Address quality escapes and fix issues in production code.
Document new methodologies and code.
Technical Skills
0-3 years work experience
Proficiency in Python, Spark, SQL
Degree in data science, statistics, engineering, applied mathematics, operations research, information sciences, or another biological/physical science.
Strength in code documentation
Proficiency in Git and code versioning tools (Gitlab).
Proficiency in Atlassian Suite such as JIRA and Confluence.
Familiarity with cloud computing (AWS, Google Cloud preferred)Knowledge of statistics and machine learning.
Ability to manipulate, analyze, and interpret large datasets.
Knowledge of dashboarding and visualization tools like Spotfire/Tableau.
