Hind Bousta

Verisure – Data Engineer | France & Spain Dec 2022 – Present Worked with international teams across France, Spain, and the UK to design, build, and optimize cloud-based data workflows using: Azure Data Factory, Azure Synapse, Snowflake, and Matillion. Key Responsibilities & Achievements: • Led a strategic cross-country project to share and synchronize Snowflake datasets between France, Spain, and the UK — overseeing both technical implementation and stakeholder coordination. • Designed and managed ETL pipelines integrating external and internal data sources. • Supported the migration from legacy systems (Sybase IQ, SAP Data Services) to modern cloud stack (Snowflake + Matillion). • Collaborated with an internal MLOps team, contributing to a custom AWS SageMaker platform used for ML model deployment. • Worked on AWS infrastructure components (Lambda, S3, IAM) for data and ML workflows. Focus: End-to-end data systems, production-ready pipelines, and bridging data engineering with MLOps.

BMW Group Financial Services – Data Analyst | France June 2021 – Nov 2022 Worked with the Risk team to collect, clean, and analyze business data, supporting decision-making and operational monitoring through analytics and dashboarding. Key Responsibilities & Projects: • Conducted credit scoring analysis and monitored the evolution of cut-off scores. • Performed statistical profiling of customers rejected by scoring models. • Built automated Tableau dashboards for:  – Fraud detection and monitoring  – Weekly tracking of customer financing requests  – Processing time KPIs from application to funding  – Data quality monitoring: measuring completeness and accuracy of warehouse tables Tools: Python, SAS, Tableau

Developed and optimized a recommender system for banking products, and contributed to customer segmentation efforts to support targeted marketing initiatives. Key Responsibilities & Projects: • Designed and improved a product recommendation system • Monitored operational testing phases and iterated on model performance. • Conducted unsupervised customer segmentation using clustering algorithms (K-means, K-medoids) to identify actionable groups for marketing strategies. • Managed data preparation and feature engineering to ensure modeling quality. Tools: Python, R, PySpark, Azure Databricks, Scikit-learn

Explored advanced Deep Learning concepts including Meta-learning, Few-shot, and One-shot learning, with practical testing on image datasets. Key Tasks: • Conducted state-of-the-art research on cutting-edge neural architectures. • Evaluated and tested learning techniques on small-sample image data. Tools: Python, PyTorch, TensorFlow

Developed NLP-based classification models to categorize user-submitted questions on the Whyse platform into general themes. Key Tasks: • Built and evaluated models using Word2Vec, spaCy, BERT, and scikit-learn (Random Forest, Boosting, Neural Networks). • Performed web scraping to enrich training datasets. Tools: Python

• Animation of lean management and continuous improvement strategies. • Data management for industrial data. • Parameterization and deployment of an ERP. • Operator training on the use of the new ERP.