Data Scientist

Summary

Join dynamic teams at Mediagenix, a company enabling media companies worldwide to efficiently deliver content. Collaborate with product teams to identify opportunities for AI-driven functionalities in internal tools and customer-facing products. Align with the Global Analytics & AI roadmap, proposing initiatives and contributing to its evolution. Partner with data engineers to define data requirements and build data pipelines. Design and develop AI models for personalization, search, and discovery features. Work with DevOps teams to establish workflows for training, testing, and deploying AI models. Create and implement monitoring solutions to track model performance. Define and implement key business KPIs and visual analytics. Enjoy a healthy work-life balance with flexible remote work, financial support for home office setup, luncheon vouchers, sustainable mobility package, extra vacation days, and more. Work in a green-minded environment with various perks and a joyful atmosphere.

Requirements

• Proven hands-on experience working with various data modalities to build AI models or develop end-to-end AI workflows
• Strong programming skills with production-ready code in Python and SQL
• Solid understanding of database systems, including relational (e.g. RDBMS), document-oriented (e.g. MongoDB), and search-based systems (e.g. Elasticsearch)
• Familiarity with big data platforms such as Snowflake, Databricks, or Apache Druid

Responsibilities

• Collaborate closely with product teams to identify opportunities where AI-driven functionalities can add value to both internal tools and customer-facing products
• Align with the Global Analytics & AI roadmap by proposing initiatives that address product needs or non-functional requirements, contributing actively to its evolution
• Partner with data engineers to define data requirements, identify source systems, and build robust data pipelines for ingestion, processing, analysis, and modeling
• Design and develop AI models and algorithms that power personalization, search, and discovery features, enhancing Spideo’s core product suite
• Work with DevOps teams to establish workflows for training, testing, and deploying AI models in production, following CI/CD best practices
• Create and implement monitoring solutions to track model performance, detect concept drift, assess data quality, and trigger model retraining when needed
• Define and implement key business KPIs and visual analytics to demonstrate the impact, effectiveness, and transparency of AI applications to stakeholders

Preferred Qualifications

• Experience in developing machine learning and deep learning models using libraries such as Scikit-learn, PyTorch, or TensorFlow
• Strong foundation in applied statistics and probability theory
• Practical experience with containerization (e.g. Docker) and Infrastructure as Code tools (e.g. Terraform)
• Proficiency with data visualization libraries and BI tools like Plotly Dash, Tableau, or Power BI
• Good knowledge of cloud platforms and services (e.g. AWS ECS, EC2, Lambda, Fargate), and exposure to AI/ML-specific frameworks like AWS Bedrock or SageMaker
• Prior experience working on Natural Language Processing (NLP) use cases is a strong asset
• Hands-on experience with distributed data and ML frameworks such as Apache Spark, Dask, or Ray is highly desirable

Benefits

• Enjoy a healthy work-life balance with a flexible remote work policy and financial support for setting up your home office (laptop, desk, chair, and more)
• Benefit from luncheon vouchers, a sustainable mobility package, extra vacation days, Alan’s contingency fund, and a 50% contribution to transport costs