Data Scientist

When you are enjoying content on TV, radio, smartphone, tablet or PC, you are also watching the works of the team that helps put that content right there. The mission of Mediagenix is to enable renowned media companies (e.g. BBC, Disney, Discovery, Paramount) worldwide to bring content to the viewer in the most efficient and future-proof way with the help of our business management system.
To support media companies in their growth in this fast-paced media world, we deliver innovative software solutions that optimize the life cycle of their content across channels and services.

Your challenge

• 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.

Your interest and skills

• Must-Have Qualifications
• 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.
• Nice-to-Have 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.

Our offer

• Join dynamic teams that foster collaboration, share knowledge, and tackle challenges together, empowering you to fully express yourself and develop your skills.
• 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.
• Work in a green-minded environment with organic and seasonal fruit, ethically sourced coffee and tea, eco-designed desks in partnership with Slean, and comprehensive recycling programs.
• Experience a joyful and caring atmosphere with spontaneous terrace gatherings, team events, lunches by the Canal, yoga sessions, a reading area, board games, and gaming consoles spanning retro classics to the latest (NES to PS5).

Excited? So are we! Take the next step by applying below and let us demonstrate the endless possibilities at Mediagenix.
We're already looking forward to meeting you!