Data Scientist

Data Scientist

Company: Cint Location: United Kingdom (Onsite) Contract: Permanent Seniority: Mid-Level

About Cint

Cint is a pioneer in research technology (ResTech). Our customers leverage the Cint platform to gather insights from real people, enabling them to build business strategies, publish research, and accurately measure digital advertising impact. Our programmatic marketplace is the world's largest, connecting with nearly 300 million respondents across over 150 countries who consent to share their opinions, motivations, and behaviours. We are dedicated to feeding the world's curiosity.

About the Role

As a Data Scientist at Cint, you will join our Data Science and Analytics teams, collaborating closely with product and engineering teams on Media Measurement and Data Solutions products. This role involves data analysis, the design of statistical and machine learning model methodologies and codebases, and model validation. We are looking for a self-starter who is comfortable working with large datasets, possesses a strong understanding of statistical and machine learning techniques, and is eager to contribute to the development and validation of products that align Cint's capabilities with market needs.

Key Responsibilities

• Contribute to the discovery and development phases for new and existing products and models related to media measurement.
• Participate in model development, validation, and maintenance.
• Analyze large datasets to identify trends, patterns, and insights, ensuring the 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 achieve broader project goals.
• Assist in developing methodologies, model validation, and the maintenance and enhancement of existing statistical and machine learning models.
• Support the evaluation and validation of both internal and external products to ensure Cint's success.
• Communicate insights and recommendations through visualizations and presentations tailored for diverse audiences.

Requirements

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

Bonus Points

• Experience in media measurement and digital attribution.
• Experience in multivariate testing.
• Experience with online survey methodologies.
• Ability to write and optimize SQL queries.
• Experience working with big data technologies (e.g., Spark).

What We Offer

Cint is recognized in Newsweek's 2025 Global Top 100 Most Loved Workplaces®, reflecting our commitment to a culture of trust, respect, and employee growth. We foster a collaborative environment where success is achieved together across borders, and innovation is driven by insatiable curiosity. We are accountable, deliver excellence, and operate with openness, honesty, and kindness. We are also committed to learning from each other, valuing every opinion, and embracing diversity, equity, and inclusion.