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Cint
Cint
1,001 – 5,000 Employees
ConsultingMarket ResearchMarketing
Cint is a global market research technology company operating the Cint Exchange, a programmatic research marketplace that connects surveys with respondents across 130 countries. Its platform supports media measurement, audience monetization, brand lift studies, advertising impact analysis, and real-time marketing optimization. Cint combines survey technology with AI and machine learning tools designed to help protect data quality and integrity, serving organizations across consulting, marketing, and market research.
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Senior Data Scientist, Brazil (Remote)

Lead statistical modeling and machine learning for Cint’s media measurement products. Turn large, complex datasets into insights that guide product strategy and development.

BRBrazilRemoteFull-timeSeniorEnglish RequiredData Scientist
PythonSparkSQL

Description

  • Design statistical methods and machine learning codebases for media measurement products.
  • Lead research, discovery, and full-cycle development of statistical and machine learning models.
  • Analyze large, complex datasets to generate insights for product strategy and roadmap decisions.
  • Manage data science initiatives from planning through maintenance with limited supervision.
  • Collaborate with engineering and product teams on the design, deployment, implementation, and validation of scalable machine learning models.
  • Build, validate, and maintain statistical and machine learning models.
  • Continuously assess and validate internal and external product methodologies.
  • Convert statistical results into visualizations and presentations for technical and non-technical audiences.
  • Present findings and statistical recommendations clearly to varied business and technical stakeholders.

Requirements

  • Master’s degree or equivalent in statistics, quantitative sciences, data science, operations research, or another quantitative discipline.
  • At least five years of data science experience, ideally in market research or advertising analytics.
  • Independence in manipulating, analyzing, and interpreting large datasets.
  • Strong command of advanced statistical concepts, including distributions, hypothesis testing, parametric and non-parametric tests, survey design, sampling theory, experimental design, regression or predictive modeling, and stochastic modeling or simulation.
  • Strong knowledge of machine learning methods, including clustering, regression, and tree-based models, along with their practical trade-offs.
  • Practical experience applying statistical and modeling techniques.
  • Strong analytical ability with careful attention to data validation and accuracy.
  • Ability to independently investigate and learn unfamiliar methods, tools, and techniques.
  • Self-directed approach to delivering projects from inception through completion with limited supervision.
  • Proficiency in Python for statistical analysis and machine learning implementation.
  • Experience with media measurement and digital attribution is advantageous.
  • Experience with multivariate testing is advantageous.
  • Experience with predictive modeling is advantageous.
  • Experience linking attitudinal survey data with behavioral purchase data to model and quantify outcomes is advantageous.
  • Experience with online survey methodologies is advantageous.
  • Ability to write and optimize SQL queries is advantageous.
  • Experience with big data technologies such as Spark is advantageous.

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