Senior Data Scientist (Forecasting & Marketing Mix Modelling)

Square Enix; England (AR); On-site; USD 130,000 - 170,000; Full time

Job summary

Square Enix is seeking a Senior Data Scientist to lead forecasting, modelling, and technology foundations for marketing and sales analytics. The role focuses on building robust tools, simulation frameworks, QA processes, and model monitoring to improve forecast accuracy and scenario planning, collaborating with data scientists, data engineers, and marketing stakeholders.

You will oversee end-to-end forecasting pipelines, design reusable components, and drive scalable solutions that impact

Qualifications

• Proficiency in Python with modular code design.
• Experience applying statistical modelling to business problems.
• Familiarity with Flask/FastAPI or similar for internal tools.
• Experience with Git and version control.
• Knowledge of cloud platforms (GCP) and data engineering basics.

Responsibilities

• Own end-to-end Forecasting process from data, modelling, and tech perspective.
• Design internal tools and reusable modelling components for forecasting solutions.
• Develop simulation and scenario planning tools for marketing investments and pricing.
• Support model performance monitoring and capture stakeholder feedback for improvements.
• Measure success by tool adoption, forecast reliability, and decision support impact.

Skills

Python

Git

Statistics modelling

Cloud computing (Google Cloud)

Modular code design (functions/classes

Education

Advanced degree in a quantitative field

Tools

Flask

FastAPI

Job description

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 highly analytical Senior Data Scientist to lead the data, modelling, and technology foundations of our Forecasting function, including Marketing Mix Modelling and media effectiveness capabilities. The role will build robust internal tools, simulation frameworks, QA processes, and model monitoring routines that improve forecasting accuracy, scenario planning, and marketing decision-making. They will work closely with project managers, analysts, data scientists, data engineers, and marketing stakeholders to prioritise and deliver practical, scalable solutions.

Responsibilities & KPI's

• Own the end-to-end Forecasting process from a data, modelling, and technology perspective, ensuring models, tools, QA routines, and monitoring are reliable, scalable, and business-relevant.
• Design internal tools, QA workflows, and reusable modelling components that help the Forecasting team build, test, iterate, and deploy forecasting and Marketing Mix Modelling solutions efficiently.
• Develop simulation and scenario planning tools that help marketing teams evaluate media investment, campaign strategies, pricing, promotions, and potential sales outcomes.
• Support and improve the model performance monitoring process, including tracking forecast accuracy, identifying systematic bias, capturing stakeholder feedback, and feeding these learnings back into model development.
• Success will be measured by the quality, adoption, and business impact of delivered tools and modelling processes, including improved forecast reliability, faster scenario turnaround, stronger monitoring, and better marketing decision support.

Key Stakeholders

• Data-Driven Insights
• Global Marketing
• Sales
• eStore
• Performance Optimization

Qualifications and Skills

Essential

Technical Skills

• Demonstratable current proficiency in mathematics (e.g. A-level Mathematics with grade A, A+ or equivalent).
• Strong delivery mindset, with the ability to work under tight deadlines and consistently drive business impact.
• Proficiency in Python, including modular code design using functions and classes, and experience with version control tools such as Git.
• Experience applying statistical modelling to business problems, including model validation, performance monitoring, and communication of model limitations.
• Experience developing internal tools or analytical applications using frameworks such as Flask, FastAPI, or similar.
• Familiarity with cloud computing platforms (e.g. Google Cloud).

Industry Knowledge (marketing and gaming)

• Understanding of game industry dynamics, including genre-specific sales patterns, platform strategies, long-tail revenue behaviour, and the impact of discounting and marketing campaigns.
• Ability to translate business logic into data-driven forecasting frameworks.
• Experience with Marketing Mix Modelling or media effectiveness analysis, including understanding how media spend, channel mix, seasonality, promotions, pricing, and external factors can influence sales or player behaviour.

Soft Skills

• Strong communication skills, with ability to explain complex concepts to both technical and non-technical stakeholders.
• Collaborative mindset and ability to work across data science, engineering, and business teams.

Desirable

• Ability to build and evaluate Bayesian models using PyMC or Stan, with a focus on real-world forecasting applications. Formal work experience not required.
• Experience in pricing analytics, demand modelling, or revenue forecasting within entertainment or consumer industries.
• Experience of managing/mentoring junior members.

Purpose & Values

• Purpose: Creating New Worlds with Boundless Imagination to Enhance People’s Lives.
• Values:
  • Deliver Unforgettable Experiences
  • Embrace Challenges
  • Act Swiftly
  • Stronger Together
  • Continuously Evolve
  • Cultivate Integrity