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Job Summary Square Enix is a leading publisher of entertainment content, known for iconic franchises such as Final Fantasy , Kingdom Hearts , Dragon Quest , NieR , Life is Strange , and Just Cause . Our mission is to create and deliver experiences that resonate deeply with the hearts and minds of our players. We are seeking a Marketing Science Manager to join our Forecasting team, with a core focus on connecting Marketing strategy with Forecast outputs. This role is responsible for translating marketing plans, awareness objectives, and promotional assumptions into quantified, decision-grade inputs used in forecasting and business planning. The role acts as the critical bridge between Marketing and Forecasting, ensuring that marketing activities are structurally modelled, transparently represented, and consistently reflected in forecast scenarios and executive decisions. In addition to hands-on analytical work, this role will mentor junior and mid-level analysts and data scientists and will work closely with the Director to ensure the quality and consistency of the team’s outputs—both in terms of model inputs and results. Learn more about the team's work: https://www.youtube.com/watch?v=Mfvf5w1AnnE https://cloud.google.com/blog/products/data-analytics/square-enix-builds-a-customer-data-platform-with-google-cloud Roles, Responsibilities, and KPIs 1.      Marketing–Forecast Integration & Learning Act as the bridge between Marketing and Forecasting, translating marketing plans and assumptions into structured, quantified forecast inputs. Define how marketing activities (e.g. campaigns, media intensity, timing, pricing and promotion) are represented in forecast models and scenarios. Ensure consistency and linkage from strategy and forecasting through execution. 2.       Modeling & Scenario Ownership Co-own the design and validation of models linking publishing activities, awareness, and demand, in close collaboration with Senior Data Scientists. Translate assumptions into coherent forecast scenarios, including defining and maintaining scenario ranges (e.g. MIN / MAX). Ensure outputs are methodologically sound, explainable, and decision-grade. 3.      Test & Learn & Continuous Improvement Design and drive a structured Test & Learn approach to validate key publishing assumptions. Incorporate learnings from experiments and observed outcomes into models and forecast inputs. Requirements Essential Technical Skills Demonstrable current proficiency in mathematics and statistics (e.g., A-level Mathematics with grade A, A+ or equivalent). Proficiency in Python, including modular code design using functions and classes. Experience building linear / non-linear response models using population and media consumption data. Familiarity with model performance monitoring and iterative improvement. Ability to translate business and marketing assumptions into quantitative models and decision-ready outputs. Industry Knowledge (marketing, media and gaming) Understanding of media planning principles and awareness KPIs. Familiarity with media data providers across EU and US markets, such as: Kantar, Ipsos, GfK, Nielsen, Comscore. Ability to assess data reliability, granularity, and accessibility across regions.  Soft Skills Strong communication skills, with the ability to explain complex concepts to both technical and non-technical stakeholders. Collaborative mindset and ability to work across data science, marketing, and external partners. Strategic thinking and independent decision-making. Desirable Experience in media mix modeling or marketing effectiveness analysis. Basic understanding of Bayesian statistics and probabilistic modeling, with the ability to apply Bayesian inference to media effectiveness, forecasting, and decision-making under uncer