Data Scientist – Panels & Survey Methodology

AudienceProject; København; On-site; DKK 650,000 - 900,000; Full time

Benefits offered by this job

Pension scheme

Health insurance

International environment

Friendly, supportive colleagues

Innovative products/services

Real-world panel/survey data

Opportunity to improve methods

Job summary

AudienceProject is seeking a Data Scientist – Panels & Survey Methodology in Copenhagen to advance cross-media audience measurement through rigorous panel and survey analysis. You will join the Data Science Research team, collaborating with 10+ data scientists and engineers to improve inputs, methods, and data quality.

You bring strong quantitative skills, Python proficiency, and an understanding of panel representativeness, bias, and measurement error.

Qualifications

• Strong skills in quantitative analysis and applied statistics, including regression, sampling, uncertainty and model validation.
• Hands-on Python skills to clean, explore and analyse real-world data independently and make your work reproducible.
• An understanding of panels and surveys, including representativeness, selection bias, non-response and measurement error.

Responsibilities

• Analyse panel composition and coverage across partners, identifying differences, gaps and potential sources of bias.
• Assess the completeness, consistency and plausibility of passive measurement data, and investigate unexpected changes.
• Design and analyse surveys that describe panelists and their behaviour and provide data for model calibration.
• Contribute to the development and evaluation of weighting, calibration, and statistical modelling approaches, testing how methodological choices affect audience estimates.
• Identify survey-response quality issues and assess the trade-off between stricter quality rules and retaining a representative sample.
• Clean, combine, and analyse panel and survey datasets in Python, with clear documentation of assumptions, methods and limitations.
• Work with panel-partner colleagues, data scientists, and engineers to turn findings into practical data-quality improvements and evaluate their effect.

Skills

Quantitative analysis

Python

Statistics

Panel methodology

Data science

Communication

Education

Quantitative education or equivalent

Tools

Python

Job description

Are you our new Data Scientist – Panels & Survey Methodology?

AudienceProject is looking for a Data Scientist – Panels & Survey Methodology for our Copenhagen office to support our continued growth.

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Are you a quantitative researcher who enjoys working with data about people? And are you interested in how panels and surveys can make audience measurement more reliable? Then, we have an opportunity for a career in a fast-growing scale-up with 100+ employees that collaborates directly with companies such as Heineken, L’Oréal, LVMH, Omnicom Media, Publicis Media, WPP Media, Amazon, Google, Netflix, RTL and Warner Bros. Discovery.

AudienceProject is a leader in independent cross-media measurement, enabling advertisers, media owners and the industry to trust, prove, and improve advertising outcomes through a scalable SaaS platform.

Our platform provides advertisers with a unified view of campaign performance, enabling confident omnichannel investment decisions, and provides media owners with comparable, third-party validation to demonstrate the value of their inventory.

After more than 15 years of leading cross-media measurement, we are now looking for a motivated Data Scientist – Panels & Survey Methodology to join our Data Science Research team.

Joining AudienceProject will give you a front-row seat in the rapidly evolving advertising industry and an opportunity to work within a respected business, delivering insights about audiences across the world's largest media channels to top-tier clients.

What you will do

You will join our Data Science Research pod, led by Jacob Daniel Kirstejn Hansen, and help turn panel and survey data into reliable audience measurement. Our panelists are recruited through several panel partners. They contribute passive measurement data through integrations and take part in surveys that help calibrate our models. You will work with 10 other data scientists and engineers, bringing together a range of academic and professional backgrounds.

Your focus will be quantitative analysis, panel quality and statistical methodology. You will use Python to investigate data and develop reproducible analyses, working closely with researchers and engineers to improve the inputs and methods behind our measurement.

We actively explore and apply AI in our internal work, production systems and products, combining experimentation with sound analytical judgement. You will help evaluate promising approaches with data scientists and developers and turn useful ideas into practical improvements.

Your key responsibilities will include:

• Analyse panel composition and coverage across partners, identifying differences, gaps and potential sources of bias.
• Assess the completeness, consistency and plausibility of passive measurement data, and investigate unexpected changes.
• Design and analyse surveys that describe panelists and their behaviour and provide data for model calibration.
• Contribute to the development and evaluation of weighting, calibration, and statistical modelling approaches, testing how methodological choices affect audience estimates.
• Identify survey-response quality issues and assess the trade-off between stricter quality rules and retaining a representative sample.
• Clean, combine, and analyse panel and survey datasets in Python, with clear documentation of assumptions, methods and limitations.
• Work with panel-partner colleagues, data scientists, and engineers to turn findings into practical data-quality improvements and evaluate their effect.

Who you are

You combine strong quantitative skills with curiosity about how people are represented in data. You enjoy tracing an unexpected result back to its source, questioning assumptions and explaining what the evidence supports. Your background may be in statistics, quantitative social science, economics, psychology, data science or another relevant field.

You bring:

• Strong skills in quantitative analysis and applied statistics, including regression, sampling, uncertainty and model validation.
• Hands‑on Python skills to clean, explore and analyse real‑world data independently and make your work reproducible.
• An understanding of panels and surveys, including representativeness, selection bias, non-response and measurement error.
• A careful approach to data quality and the ability to judge how data issues affect an analysis or model.
• The ability to explain methods and findings clearly to both technical and non‑technical colleagues.
• A relevant quantitative education or equivalent applied research experience.

Useful additional experience includes weighting, calibration or passive behavioural data.

We value thoughtful analysis, openness to different perspectives and colleagues who share what they learn. You ask questions, test assumptions and explain your conclusions clearly.

What we offer

You will join a curious, collaborative and energetic environment where data scientists and developers share ideas and learn from one another. Different perspectives help us ask better questions and improve how we measure audiences.

Our social calendar offers plenty of opportunities to get to know colleagues, with activities you can choose to join. There is room to contribute your ideas, take on meaningful research questions and develop your skills with the support of colleagues.

• Pension scheme and health insurance
• International environment
• Friendly, supportive and helpful colleagues
• Innovative and market‑leading products and services
• Real‑world panel and survey data, with research questions about quality, representativeness and uncertainty
• The opportunity to improve the statistical methods behind independent audience measurement
• Working directly with some of the most modern and successful companies of our time

We welcome different routes into data science. If this role interests you and you bring relevant quantitative and Python skills, we would like to hear from you.

If you have any questions about the position, please contact Jacob Daniel Kirstejn Hansen at [e-mail].