Staff Data Scientist

Company Description

Who We Are

Cint is a pioneer in research technology (ResTech). Our customers use the Cint platform to post questions and get answers from real people to build business strategies, confidently publish research, accurately measure the impact of digital advertising, and more. The Cint platform is built on a programmatic marketplace, which is the world's largest, with nearly 300 million respondents in over 150 countries who consent to sharing their opinions, motivations, and behaviours.

We are feeding the world's curiosity!

Job Description

As a Staff Data Scientist at Cint, you will be responsible for designing and developing advanced statistical and machine learning methodologies across our Media Measurement and Data Solutions product lines. You will lead high-impact initiatives, guide cross-functional collaborations, and serve as a subject matter expert on data science methodologies that support our product suite.

You are expected to work independently across multiple complex projects, help shape data science strategy, mentor and coach team members, and translate business challenges into scalable, data-driven solutions. Your work will ensure that our data science solutions are robust, scalable, and aligned with both market demands and company objectives.

Key Responsibilities:

• Develop and deploy statistical models, machine learning algorithms, and custom analytics solutions to measure the effectiveness of media campaigns.

• Collaborate with cross-functional teams to design, refine and automate measurement methodologies for TV, digital, social, and other media platforms.
• Lead the research and discovery phases for both new and existing products and partner closely with engineering teams to transition prototypes into robust, scalable solutions.
• Develop customer-facing methodology resources and thought leadership. Support business teams in explaining and defending our measurement methodologies broadly to customers.
• Plan, develop, and manage projects from concept to completion with no supervision, ensuring timely and high-quality delivery.

• Partner with product teams and other stakeholders to translate business needs into actionable data science initiatives.

• Serve as a technical leader and mentor to other data scientists in the team, promoting best practices in coding, experimentation, and analytical techniques.
• Stay up to date with the latest industry trends and emerging methodologies in media measurement and data science.

• Communicate complex results, insights and strategic recommendations to both technical and non-technical audiences through compelling data visualizations, detailed reports and presentations

Qualifications

Qualifications:

• Advanced degree (Ph.D. or Master's) in a quantitative field such as Data Science, Statistics, Mathematics, Operations Research, Economics, Computer Science, or Quantitative Sciences with outstanding analytical expertise
• 7+ years of experience in data science and analytics, machine learning, model development/validation, or related fields, with at least 2 years focused on media measurement, marketing analytics, or advertising.
  
  • Proven track record in leading large-scale data science projects, mentoring teams, driving strategy and delivering business impact.
• Demonstrated experience in advanced statistical techniques and concepts
  
  • e.g., properties of distributions, hypothesis testing, multivariate (parametric/ non-parametric) testing, sampling theory, weighting/projection, experimental design, regression/predictive modeling, causal inference techniques, stochastic modeling / simulation, and more.
• Strong programming skills in Python (as it relates to statistical analysis and implementing Machine Learning models)
• Proven expertise in advanced Python prototyping
• Proficiency with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and techniques (e.g., clustering, regression, tree-based models)
• Advanced SQL skills and familiarity with big data technologies (Spark, Hadoop, Databricks).
• Demonstrated ability to independently and confidently carry out projects end-to-end.
• Understanding of infrastructure cost management, particularly in relation to processing large datasets efficiently.

Preferred Qualifications:

• Experience in online survey methodologies

Additional Information

Personal Attributes:

• Excellent communication skills and advanced presentation skills, with the ability to explain complex technical concepts to large technical and non-technical audiences.
• Excellent interpersonal skills, ability to work effectively with cross-functional teams and stakeholders.
• Strong ability to analyze complex and large data sets and extract meaningful insights.
• A genuine interest in exploring new data science methods, tools, and technologies to create and implement innovative solutions and approaches.

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Our Values

Collaboration is our superpower

• We uncover rich perspectives across the world
• Success happens together
• We deliver across borders.

Innovation is in our blood

• We're pioneers in our industry
• Our curiosity is insatiable
• We bring the best ideas to life.

We do what we say

• We're accountable for our work and actions
• Excellence comes as standard
• We're open, honest and kind, always.

We are caring

• We learn from each other's experiences
• Stop and listen; every opinion matters
• We embrace diversity, equity and inclusion.

More About Cint

We're proud to be recognised in Newsweek's 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 world's 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. (www.cint.com)
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