The Marketing Science measurement team is charged with driving good measurement, demonstrating the return on ad spend/value of the platform, developing best practices and informing product development.Meta is seeking a highly quantitative measurement professional, with analytics experience to drive our measurement strategy with sophisticated clients in EMEA and Globally. The Marketing Science Analyst will work with internal stakeholders to advise specific clients on measurement strategy, working with them on an ongoing basis to consistently improve business performance through the use of data and science.The successful candidate will demonstrate strong analytical and critical thinking skills and have a passion for data driven decision making. They will be responsible for working with other Marketing Science Partners, Sales teams and critical cross functions such as Solutions Engineering and Product teams to perform in-depth analysis, research studies and design tests to help understand and improve the effectiveness of clients advertising across digital platforms and other media.The ideal candidate will be passionate about Meta and online advertising, intellectually curious, a fast learner and able to move fast while keeping focused on high impact projects. They should demonstrate a strong understanding of the media landscape and ability to apply quantitative techniques and innovative technical solutions to understand consumer behaviour and advertising effectiveness through experimental analytics, methodologies and products.This position is full time and located in Amsterdam
Marketing Science Data Scientist / Analyst Responsibilities:
Responsible for working with the wider Meta teams to support the marketing strategy for key clients in EMEA and globally.
Develops and executes analytical strategy for complex client, sub vertical or vertical, or geography and exercises judgment to evaluate potential projects.
Build high quality solutions (implementing the required queries, pipelines, and visualisations) using Meta's data tools and frameworks, which involves the ability to self-learn.
Develops innovative approaches and solutions by listening and prioritising market feedback that reflects deep technical expertise
Provide technical and thought leadership on designing, prototyping, implementing and automating complex analyses. End-to-end analyses, from data requirement gathering, to data processing and modelling.
Provide feedback to and collaborate with Product, R&D and Solutions Engineering to identify opportunities for new features, products and partnerships driving engagement around measurement innovation, including products alphas and beta.
Effectively communicate complex research results to a general audience.
Conduct in-depth and custom ad effectiveness studies to understand and improve the relative impact of different marketing strategies across digital platforms and across media.
Supports the Marketing Science colleagues with analysing data and identifying appropriate tools and methods to provide a simple and effective solution to problems
Moves clients and areas under their leadership (geographies, subverticals, clients, etc.) through analytical projects leading to behavior change in some client functions/areas
Minimum Qualifications:
Bachelor’s degree or equivalent required, a degree in statistics, economics, engineering, computer science, behavioral or social science or a related quantitative degree.
Experience and knowledge in predictive modelling, machine learning, experimentation methods
Able to conduct bespoke analysis, ability to build pipelines and handle large structured or unstructured datasets to understand patterns and provide client insights.
Familiar with base statistical concepts such as regression, time series, decision trees and experience with statistical analysis, including but not limited to experimental design, modelling, or advertising research
Previous experience working with large data sets, data integrations, API coding and statistical software such as R, MATLAB, SPSS, SAS, STATA, PHP, Python, hive, Tableau and SQL to structure, transform and visualise data.