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Engineering / Media / Quality
Senior Data Scientist (01504) Remote
Nielsen Global Media collects billions of data points on what consumers watch and buy. We study consumers in more than 100 countries, and help our clients globally identify unmet needs, develop new products and deliver them in an engaging way. We are constantly evolving, not only in terms of where we measure, or who we measure, but in how our insights can help drive profitable growth.
DESCRIPTION
Develop and apply machine learning and predictive models to enhance digital measurement.
Engineer predictive features for use in our current data modeling pipelines. Manage projects through all phases, including data quality, analysis design, algorithm/feature development, predictive modeling, summarization, visualization, and communication of results.
Enhance and evolve existing solutions to meet changing business needs with agility. Independently develop custom production level Python and SQL code.
Use Git and cloud development tools extensively to iterate and improve data science work streams. Write well documented production level Python scripts and participate in code reviews.
Collaborate with our software engineers and product leaders as you integrate and test new or updated modules in production pipelines. Identify gaps in data capture or data quality, and surface the value attached to filling those gaps.
Perform deep dive analysis of key business trends from different perspectives and package the insights into easily consumable presentations and documents using visualization tools such as Tableau. Serve as critical Data Science subject matter expert, initiate methodology discussions with relevant stakeholders, and provide final Data Science recommendations.
Remote work permitted five (5) days a week from within New York area, NY.
Engineer predictive features for use in our current data modeling pipelines. Manage projects through all phases, including data quality, analysis design, algorithm/feature development, predictive modeling, summarization, visualization, and communication of results.
Enhance and evolve existing solutions to meet changing business needs with agility. Independently develop custom production level Python and SQL code.
Use Git and cloud development tools extensively to iterate and improve data science work streams. Write well documented production level Python scripts and participate in code reviews.
Collaborate with our software engineers and product leaders as you integrate and test new or updated modules in production pipelines. Identify gaps in data capture or data quality, and surface the value attached to filling those gaps.
Perform deep dive analysis of key business trends from different perspectives and package the insights into easily consumable presentations and documents using visualization tools such as Tableau. Serve as critical Data Science subject matter expert, initiate methodology discussions with relevant stakeholders, and provide final Data Science recommendations.
Remote work permitted five (5) days a week from within New York area, NY.
QUALIFICATIONS:
Master’s degree (foreign equivalent degree acceptable) in Mathematics, Statistics, Computer Science, Engineering, Machine Learning, Information Science or related field and two (2) years of experience in a data science role. Must have two (2) years of experience in/with: advanced coding in Python and SQL; code development using Git and code versioning; cloud-based environments, including AWS; Microsoft Excel or Google Sheets; and Tableau; building and maintaining Machine Learning or Deep Learning based methodologies. Remote work permitted five (5) days a week from within New York area, NY.
Salary: $119,600 to $155,000/year, M-F, 40 hours a week.
Salary: $119,600 to $155,000/year, M-F, 40 hours a week.
About Nielsen:
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.
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