Job Summary:
Square Enix is a leading publisher of entertainment content, known for iconic digital game franchises such as the Final Fantasy series, 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 passionate and driven Data Scientist to join our dynamic team. The ideal candidate should possess a strong interest in analytics, machine learning, artificial intelligence, and project management within the AI domain. This role will focus on, but is not limited to, the following areas:
- Machine learning /statistics-based applications for marketing, such as recommender systems and sales modeling
- Leveraging generative AI to enhance work efficiency
- Facilitating the success of AI/ML projects via project management, cross-team collaboration and fostering internal partnerships
A key responsibility in this role will be to initiate and oversee AI/ML projects from conception to completion. You will need to accurately assess business needs, make strategic decisions on whether to develop in-house solutions, utilize existing internal tools, or explore external options. Once a project is underway, you will design proof-of-concept (PoC) solutions, evaluate their effectiveness, and guide them to full production implementation.
In this position, you will collaborate closely with data scientists, machine learning engineers, and AI experts both within and outside the team. Additionally, you will work alongside business stakeholders to ensure AI solutions meet their objectives and deliver measurable value.
Requirements
Key Deliverables:
- Develop machine learning applications, such as recommender systems and marketing ROI optimiser.
- Leverage generative AI technologies to improve work efficiency and streamline processes across the organization.
- Facilitate cross-team collaboration on AI projects, building strong internal partnerships to drive innovation and project success.
- Initiate and manage AI projects from start to finish, including the accurate assessment of business needs and strategic decision-making (build, buy, or reuse).
- Design and implement proof-of-concept (PoC) AI/ML solutions, evaluating their impact and effectiveness to guide them into production.
- Collaborate with data scientists, machine learning engineers, and AI experts, both within the team and externally, to ensure high-quality AI solutions.
- Work closely with business stakeholders to ensure AI/ML systems align with business objectives and deliver measurable value.
- Assess data needs and engineering requirements, working closely with data scientists, engineers, and other technical teams to define data sources, models, and infrastructure requirements.
- Onboard third-party vendors or partners as needed, managing relationships, and ensuring adherence to project requirements and timelines.
- Maintain awareness of industry trends and emerging technologies, applying them where appropriate to drive business outcomes.
- Performance Measures: Project delivery, execution, adherence to project requirements and timelines, project alignment with business objectives and stakeholder satisfaction, and reliability and quality of recommended solutions, ongoing demand and adoption rate of AI-powered projects, contribution to thought leadership around the organization.
Key Stakeholders:
Analytics, IT, Legal, Community & Service, Digital Channels, Intelligence
Knowledge & Experience:
Essential:
- Proven experience as a Data Scientist, Data Analyst or Product Engineer.
- Experience with the management of ML code base and experimentation result in an organized and efficient manner
- Experience with cloud platforms and technologies for deploying and managing machine learning models at scale, such as AWS, Azure, or Google Cloud Platform
- Proficiency in data analysis, data mining and programming languages, preferably SQL and Python.
- Having worked with TensorFlow, PyTorch or scikit-learn.
- Strong understanding of machine learning algorithms, AI technologies, and predictive modeling techniques, with the ability to translate business needs into technical requirements
- Experience defining and developing a new product or service within the data space
- Desirable:
Strong understanding of Generative AI tools and APIs preferred - Working knowledge of methodologies used in recommender system such as Collaborative Filtering, Content Based Recommendation, Matrix Factorization a strong plus
- Practical experience in ML ops, such as Python packaging, Docker/Kubernetes, CI/CD, deployment and monitoring of ML models’ performance a strong plus
Our goal at Square Enix is to hire, retain, develop and promote the best talent, regardless of age, gender, race, religious, belief, sexual orientation or physical ability.
Our pledge to D&I
At Square Enix we believe in the importance of being a diverse and global company, and we stand firmly together against any forms of injustice, intolerance, harassment or discrimination. In our effort to create a truly diverse workforce, we pledge to continue to raise awareness in every step of the employee experience, from recruitment to promotions to ensure equal opportunities for all. One of our goals is to champion diversity in games and at work and work together to inspire real change.
Learning and education around D&I will be a key element for us to continue to grow as an organization. With unconscious bias training, D&I workshops and a variety of initiatives to give our employees the opportunity to be heard and be part of that change to achieve real equality. We need all our efforts to continue to build our culture of inclusion and equality.
We are also proud to partner with UKIE's Raise the Game pledge, BAME in Games and Women in Games, to name a few.
Hybrid Working Policy
Square Enix is pleased to be an employer that offers flexibility within the workplace.
We have a hybrid working policy which allows employees to work from the comfort of their home, three days per week, and in our amazing Blackfriars office for the other two.
Or, if being in the Office is your preference, you can choose three days working from our office and two days working from home. The choice is yours!
