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Nielsen
Nielsen
H1B vīzas sponsorsDatu analītikaMārketingsPlašsaziņas līdzekļi
Nielsen ir globāls mediju mērīšanas un datu analītikas uzņēmums, kas palīdz uzņēmumiem izprast auditorijas televīzijā, digitālajās platformās, straumēšanas pakalpojumos un audio medijos. Nielsen ONE piedāvājums apvieno dažādu mediju mērījumus, lai sniegtu skaidrāku priekšstatu par to, kā cilvēki patērē saturu un kā darbojas mediju kampaņas. Uzņēmums apvieno plaša mēroga datu infrastruktūru ar uz paneļiem balstītām metodēm, lai iegūtu ieskatus par patērētāju uzvedību, mediju plānošanu un mārketinga efektivitāti. Nielsen darbība aptver medijus, datu analītiku un mārketingu, īpašu uzmanību pievēršot iekļaujošai darba videi, ko veicina daudzveidīgas komandas un darbinieku biznesa resursu grupas.
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Vakances uzņēmumā

Data Scientist in Mexico (Remote)

Develop statistical and machine learning models for Nielsen’s media audience measurement business. Build production data pipelines and deliver analytics that address client needs.

MXMeksikaAttālinātiPilna slodzeVidējais līmenisVecākais speciālistsNepieciešamā Valoda: angļuDatu zinātnieks
AWSMākonisOraclePySparkPythonSQLTableau

Apraksts

  • Design, develop, implement, and test econometric, statistical, optimization, and machine learning models
  • Create forecasting models and code for PPM Wearables audience measurement production processes
  • Build data pipelines, conduct analyses, and communicate findings
  • Partner with stakeholders to develop clear, data-driven recommendations and solutions
  • Develop expertise in PPM sampling methodology, audience measurement, and panel management strategies
  • Query large relational databases to support analyses and requests
  • Perform complex data analysis and visualization with Python, Tableau, R, and comparable tools
  • Maintain and improve data algorithms for PPM sample methodology in a time-sensitive production environment
  • Maintain and revise departmental procedures, checklists, and performance metrics
  • Contribute to cross-functional teams and critical projects involving requirements definition, software development, and testing
  • Address internal and external client requests with data-driven solutions
  • Implement quality checks to identify and correct errors in production processing and analysis
  • Lead code reviews and encourage modular code, unit testing, and CI/CD practices to support product quality, stability, and scalability

Prasības

  • Bachelor’s degree or higher in mathematics, statistics, computer science, data science, data engineering, or a related discipline
  • At least 3 years of professional experience in statistics, data science, or a related field
  • At least 3 years of experience manipulating, analyzing, and interpreting complex data sources
  • At least 3 years of experience using Python, PySpark, and SQL to develop data pipelines
  • At least 3 years of experience creating data visualizations with Tableau or comparable tools
  • Experience working in cloud environments such as AWS
  • Experience with DevOps tools, source control, and CI/CD workflows using GitLab or similar platforms
  • Ability to manage projects and prioritize multiple assignments
  • Clear communication skills and the ability to manage competing priorities in a fast-paced environment
  • Willingness to evaluate new solutions and iterate quickly in response to customer feedback
  • Strategic perspective and an understanding of how data insights influence product and business objectives
  • Exceptional problem-solving ability
  • Ability to work independently and solve problems within cross-functional teams
  • Preferred: working knowledge of ANOVA, chi-squared tests, correlation, regression, and Student’s t-test
  • Preferred: experience querying large datasets with SQL and working with Oracle, Netezza, data warehouse, and data lake structures

Priekšrocības

  • Opportunity to work remotely
  • Equal-opportunity employer with a diverse and inclusive workplace
  • Opportunity to contribute to high-impact media measurement projects with global teams

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