Data Scientist

Cint

Data Scientist role at Cint analyzing datasets and developing statistical models. Collaborating with teams on Media Measurement and Data Solutions products while ensuring quality and reliability of results.

Posted 4/16/2026full-timeRemote • 🇧🇷 BrazilJuniorMid-LevelWebsite

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Contribute to discovery and development phases for new and existing products/models relating to media measurement
Participate in model development, validation and maintenance
Analyze large datasets to identify trends, patterns, and insights, ensuring quality and reliability of results.
Respond to ad hoc client-specific requests including performing analyses, data manipulation and producing summary results.
Collaborate with cross-functional teams to deliver on broader project goals.
Participate in developing methodologies, model validation, and maintenance and enhancement of existing statistical and machine learning models.
Support evaluation and validation of both internal and external products to ensure Cint’s success.
Communicate insights and recommendations through visualizations and presentations that will resonate with a wide range of audiences.

Requirements

What you’ll need

Master’s degree or equivalent in Statistics, Quantitative Sciences, Data Science, Operations Research or other quantitative fields.
2 years of experience in a data science and analytics capacity, preferably in market research, or advertising analytics.
Ability to manipulate, analyze, and interpret large data sources independently.
Familiarity with core statistical concepts and techniques (e.g. properties of distributions, hypothesis testing, parametric/non-parametric tests, survey design, sampling theory, experimental design, regression/predictive modeling, classification, stochastic modeling/simulation, and more).
Exposure to a variety of machine learning methods (clustering, regression, tree-based models, etc.) and their real-world advantages/drawbacks.
Practical experience applying statistical and modeling techniques.
Strong analytical skills with a focus on data and model validation and accuracy.
Comfortable with learning new methods, tools, and techniques.
Able to complete assigned tasks independently while collaborating on overall project direction and broader project goals.
Proficiency in Python (as it relates to statistical analysis and implementing Machine Learning models).

Benefits

Comp & perks

Flexible work arrangements
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data analysisstatistical modelingmachine learningdata manipulationregression modelingclassificationclusteringexperimental designhypothesis testingPython

Soft Skills

analytical skillscollaborationcommunicationindependenceproblem-solvingadaptabilityattention to detailpresentation skillscritical thinkinginsight generation

Certifications

Master’s degree in StatisticsMaster’s degree in Data ScienceMaster’s degree in Quantitative SciencesMaster’s degree in Operations Research