Data Scientist

Asenium Consulting; Brussel; Hybride; EUR 90 000 - 140 000; Plein temps

Résumé du poste

Asenium Consulting in Brussels is seeking an experienced Data Scientist to join an AI team on a 16-month fraud detection project. The role emphasizes production-grade AI applications and advanced fraud detection, starting as soon as possible with a 50% hybrid work model.

You will collect, label, curate, and engineer data, design and deploy fraud models using ML, graph analytics, anomaly detection, and behavioral analytics, and collaborate with cross-functional teams to combat fraud at scale.

Qualifications

• 7+ years in data science with fraud focus.
• 5+ years building AI applications.
• Proficient in Python, Pandas and SQL.
• Extensive experience with Spark, Hadoop and distributed processing.
• Experience collecting, enriching and validating complex transactional data.
• Experience with supervised and unsupervised ML.
• Experience with anomaly detection, graph analytics, network analysis and behavioral analytics.
• Experience deploying AI in production.
• English proficiency.

Responsabilités

• Collect, label, curate, structure, and engineer data for fraud models.
• Design and improve fraud detection models with ML, graph analytics, anomaly detection.
• Transform large transactional and customer data into actionable fraud intelligence.
• Feature engineering, data enrichment, pattern discovery.
• Collaborate with Fraud Operations, Risk, Compliance, and Product teams.
• Translate business needs into scalable analytical solutions.
• Investigate complex fraud schemes and uncover attack vectors.
• Develop detection strategies to mitigate risks.
• Deploy AI applications in production.

Connaissances

Data science

Fraud detection

AI applications development

Machine learning (supervised/unsuperv)

Outils

Python

Pandas

SQL

Spark

Hadoop

Description du poste

We are looking for an Data Scientist to join an AI team in Brussels for a 16-month fraud detection project. The role follows a 50% hybrid work model and focuses on developing production-grade AI applications and advanced fraud detection solutions. The start date is as soon as possible.

Key responsibilities

• Collect, label, curate, structure, and engineer data to improve fraud detection models.
• Design, develop, and continuously improve fraud detection models using machine learning, graph analytics, anomaly detection, and behavioral analytics.
• Transform large volumes of transactional and customer data into actionable fraud intelligence.
• Perform feature engineering, data enrichment, and pattern discovery.
• Collaborate with Fraud Operations, Risk, Compliance, and Product teams to identify emerging fraud trends.
• Translate business needs into scalable analytical solutions.
• Investigate complex fraud schemes and uncover new attack vectors.
• Develop detection strategies to mitigate financial and reputational risks.
• Contribute to deploying AI applications in production.

Must-Have Requirements

• You have at least 7 years of experience in data science, with a focus on fraud detection.
• You have at least 5 years of experience developing AI applications.
• You have strong hands-on experience with Python, Pandas, and SQL.
• You have strong experience processing large-scale datasets with Spark, Hadoop, and distributed data processing technologies.
• You have experience collecting, enriching, structuring, and validating complex transactional and behavioral data.
• You have experience with supervised and unsupervised machine learning.
• You have experience with anomaly detection, graph analytics, network analysis, and behavioral analytics.
• You have experience building data-centric AI solutions using robust software engineering practices.
• You have experience deploying AI applications in production.
• English proficiency