Description

About Ludeo

Ludeo is a hyper-growth startup in the gaming industry that is revolutionizing the way players discover and engage with games. Now and for the first time, gamers can share their most thrilling gameplay moments with everyone and everywhere and allow others to PLAY them, not only watch them as video clips. Ludeo’s vision is to become the world’s first playable social media platform for gamers where they can frictionlessly discover gaming content.

About the Role

We’re seeking an experienced, hands-on Data Scientist to lead the development and deployment of our recommendation and personalization systems. You'll play a crucial role in ensuring that each user discovers the Ludeos that perfectly match their interests and gaming style.

The ideal candidate is passionate about building intelligent systems that connect users with content they'll love, has strong technical skills, and brings a collaborative approach to solving complex problems.

What you'll do

• Design, implement, and optimize recommendation and matching algorithms to connect users with the most relevant Ludeo content
• Lead the development of personalization features that enhance user experience and engagement
• Build and deploy machine learning models for content classification, user modeling, and preference prediction
• Work closely with engineering teams to implement models in production environments
• Analyze user behavior data to identify patterns and opportunities for improving recommendation quality
• Develop metrics and A/B tests to evaluate and optimize recommendation performance
• Collaborate with product teams to understand user needs and translate them into technical solutions
• Research and implement state-of-the-art approaches in recommendation systems and personalization

Requirements

• Bachelor's degree (or higher) in Computer Science, Computer Engineering, Data Science, or related field
• 5+ years of hands-on experience in machine learning and data science
• Proven experience developing recommendation systems, matching algorithms, or personalization features
• Strong programming skills in Python and experience with ML frameworks like PyTorch or TensorFlow
• Experience deploying ML models to production environments
• Strong understanding of recommendation algorithms (collaborative filtering, content-based filtering, hybrid approaches)
• Experience with large-scale data processing and analysis
• Knowledge of transformer architectures and their applications
• Excellent communication skills and ability to explain complex concepts to non-technical stakeholders

Nice to Have

• Experience with MLOps tools and practices
• SQL expertise and experience with big data technologies
• Experience with time series data analysis and forecasting
• Backend experience