Data Scientist, Audience Analytics

The Data Scientist, Audience Analytics, will be responsible for gathering and analyzing customer data of a game portfolio, developing machine learning algorithms, working closely with business stakeholders, to provide clear insights about consumer behaviors, deliver strategic recommendations and build audience centric tools. You will be the main point of contact of marketing teams, translating their need into analytical and scientific projects, and using machine learning methods to provide them insights and support them all along the life of the game, on different business needs.

Audience Analytics team works with the business stakeholders such as CRM, Paid Media, AAA brand, Live brand and F2P teams located worldwide. Our goal is to support business stakeholders and strategic decisions by delivering them analytical insights about the consumer database and providing them a clear and granular snapshot of our players at a game, brand or transversal level.

What you'll do

• Create, manage and distribute data and insights utilizing analytics tools.
• Analyze customer data to gather knowledge, generate insights, create value and support decision-making.
• Lead the development of data science initiatives that leverage audiences, support business objectives and improve customer knowledge
• Build and deploy machine learning models to predict player behavior
• Be the main point of contact of the stakeholder teams;
• Understand the brand and marketing objectives and the major initiatives;
• Identify the most relevant methodology to answer the need;
• Deliver insight; Support stakeholders in leveraging DS solutions
• Contribute innovative ideas and best practices to enhance data science methodologies within the team.

What you'll bring

• Proficient in Python & SQL
• Experience working with lakehouse data platform (Databricks, Snowflake…)
• Strong analytical and synthesis skills; ability to analyze raw data, draw conclusions, and develop actionable and strategic recommendations
• Machine Learning – Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.
• Proactivity, critical thinking and creativity with data
• A highly collaborative spirit + excellent communication, interpersonal, and presentation skills
• Excellent communication skills
• Fluency in both French and English