Data Scientist: ML, NLP, & MLOps for Impact

Appsierra Group; Brussel; Sur place; EUR 60 000 - 90 000; Plein temps

Résumé du poste

Appsierra Group is seeking a Data Scientist to design advanced analytics solutions, build ML and NLP models, and drive data-driven business insights. You will create scalable data pipelines, engineer training data via ETL, and validate models with rigorous experiments.

You will collaborate with cross-functional teams, present findings to stakeholders, and help translate business problems into sophisticated data science solutions.

Qualifications

• 3+ years of experience in data science or analytics.
• Strong knowledge of advanced analytics, machine learning, and NLP.
• Proficiency in programming languages commonly used for modeling (Python, R, etc.).
• Experience with MLOps practices and model reproducibility.
• Familiarity with ETL, data engineering, and scalable data storage technologies.
• Excellent presentation and stakeholder communication skills.

Responsabilités

• Design and implement data-driven solutions using advanced analytics techniques.
• Build predictive models and text-based models leveraging ML and NLP.
• Develop and maintain reproducible ML pipelines following MLOps practices.
• Prepare and engineer training datasets via ETL processes and data engineering.
• Architect scalable data storage solutions for AI workloads.
• Validate models through experimental design and hypothesis testing.
• Visualize and communicate model outputs using BI tools.
• Collaborate with cross-functional teams to translate business problems into DS solutions.

Connaissances

Experience in data science/analytics

Advanced analytics, ML, NLP

Python, R modeling

MLOps and reproducibility

ETL and data engineering

Data storage for AI

Presentation and stakeholder comms

Outils

Python

R

Description du poste

Appsierra Group is seeking a Data Scientist to design advanced analytics solutions, build ML and NLP models, and drive data-driven business insights. You will create scalable data pipelines, engineer training data via ETL, and validate models with rigorous experiments.

You will collaborate with cross-functional teams, present findings to stakeholders, and help translate business problems into sophisticated data science solutions.