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1 Vacancy
The Opportunity
As a Data Scientist at Cint you will have the opportunity to work alongside our Data Science and Analytics teams and collaborate with product and engineering teams to work on Media Measurement and Data Solutions products. This includes data analysis design of statistical and machine learning model methodologies and codebases and model validation. The ideal candidate is a self-starter comfortable working with large datasets and knowledgeable in statistical and machine learning techniques with an eagerness to learn and contribute to the development and validation of products that align Cint capabilities with the market.
What you will do
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 Cints success.
Communicate insights and recommendations through visualizations and presentations that will resonate with a wide range of audiences.
Qualifications :
What we are looking for
Masters 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 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 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
Bonus points if you have
Experience in media measurement and digital attribution
Experience in multivariate testing
Experience in online survey methodologies
Ability to write and optimize SQL queries
Experience working with big data technologies (e.g. Spark)
Additional Information :
Anticipated Salary Range (US Only):
The anticipated pay range for this role is $116800 to $175200 annual base salary. This position is also eligible for the following benefits:
Medical Dental and Vision insurance options to suit you and your familys needs
401K with company matching
PTO unlimited sick days
Remote Work
Paid maternity and paternity leave
Annual bonus opportunity
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Our Values
Collaboration is our superpower
Innovation is in our blood
We do what we say
We are caring
More About Cint
Were proud to be recognised in Newsweeks 2025 Global Top 100 Most Loved Workplaces reflecting our commitment to a culture of trust respect and employee growth.
In June 2021 Cint acquired Berlin-based GapFish the worlds largest ISO certified online panel community in the DACH region and in January 2022 completed the acquisition of US-based Lucid a programmatic research technology platform that provides access to first-party survey data in over 110 countries.
Cint Group AB (publ) listed on Nasdaq Stockholm this growth has made Cint a strong global platform with teams across its many global offices including Stockholm London New York New Orleans Singapore Tokyo and Sydney. ()
Remote Work :
Yes
Employment Type :
Full-time
Remote