Cint
Cint
Cint — 130 елдегі сауалнамаларды респонденттермен байланыстыратын бағдарламалық зерттеу нарығы Cint Exchange платформасын басқаратын жаһандық нарықты зерттеу технологиясы компаниясы. Оның платформасы медианы өлшеуді, аудиторияны монетизациялауды, бренд әсерін зерттеуді, жарнаманың ықпалын талдауды және маркетингті нақты уақыт режимінде оңтайландыруды қолдайды. Cint сауалнама технологиясын деректердің сапасы мен тұтастығын қорғауға арналған жасанды интеллект және машиналық оқыту құралдарымен біріктіріп, консалтинг, маркетинг және нарықты зерттеу салаларындағы ұйымдарға қызмет көрсетеді.

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.

Сипаттама

  • 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.

Талаптар

  • 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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