Senior Applied Data Scientist (AI)

TL;DR

Senior Applied Data Scientist (AI): Developing Data Science & ML algorithms to solve complex real-world business problems with an accent on GenAI, classical ML, and end-to-end pipeline automation. Focus on translating analytical findings into actionable business insights and implementing production-ready ML models.

Location: Fully Remote. Must have the right to work in one of the following countries: Belgium, Italy, Portugal, Hungary, Slovakia, or Germany

Company

Market leader in enabling digital success for small and medium-sized businesses (SMBs) across Europe, serving over 3 million customers.

What you will do

• Break down multi-domain business problems into technical methods from POC to production with a focus on ROI.
• Develop solutions and extract insights using classical ML methods and Generative AI (GenAI).
• Take ownership of the full ML lifecycle, including feature generation, modeling, evaluation, retraining, and deployment.
• Translate sophisticated analytical findings into actionable insights to drive key business metrics.
• Collaborate with cross-functional teams to deliver innovative AI/ML solutions.
• Research and apply the latest Data Science and AI developments to improve internal systems.

Requirements

• 8+ years of hands-on industry experience solving real-world ML problems across multiple verticals.
• Expert proficiency in Python and SQL, and experience with frameworks like Scikit-learn, Pandas, and PyTorch.
• Deep understanding of algorithms ranging from SVMs to Deep Learning and LLMs.
• Ability to own the end-to-end lifecycle of AI projects, including containerization.
• Proven track record of implementing projects that have been put into production and created impact.
• Proof of eligibility to work in the applied country (no visa sponsorship or relocation provided).

Nice to have

• Master's or PhD in Computer Science, AI, Physics, Applied Mathematics, or related fields.
• Knowledge of DataOps & MLOps practices, including model monitoring and ETL pipelines.
• Experience with distributed data tools (Spark, Dask, Apache Arrow) and observability frameworks (OTel).
• Experience working in both startup and enterprise environments.

Culture & Benefits

• Inclusive "Come as you are" culture valuing respect, openness, and collaboration.
• Commitment to ESG (Environmental, Social, and Governance) and ambitious sustainability goals.
• Fully remote work arrangement.
• Diverse and international environment operating in 25+ languages.