Adel Basli

• Managed design and implementation of data science and deep learning systems, achieving a 35% improvement in system efficiency and a
20% increase in data accuracy.
• Collaborated with engineers and product managers to establish data science goals and practices for a 5-person team, increasing team productivity by 25% and reducing delivery times by 15%.
• Led strategic code implementation for 50+ daily deployments, achieving a 30% increase in deployment success rate.
• Managed financial operations (FinOps) for cost-effective data science solutions, reducing operational costs by 20% while maintaining
performance.
• Prioritized data initiatives based on ROI alignment with business goals.
• Created data visualizations for effective communication of complex insights.
• Implemented Elasticsearch to improve data accuracy, reducing manual decision-making by 10%.

• Led Scrum ceremonies, promoting Agile methodologies.
• Developed AI-based classifier with LLM, saving $3MM/yr in data transformation costs.
• Deployed scalable real-time data system on AWS, reducing processing time by 40% and ensuring fault tolerance. • Used Amazon Personalize for real-time recommendations, increasing CTR by 30% and AOV by 25%.
• Stayed updated with industry trends, implementing innovative data science solutions using generative AI.

• Led a team of 6 in supporting complex machine learning application rollout across 9 servers.
• Implemented CI/CD in cloud migration, improving Mean Time to Repair (MTTR) by 80%.
• Directed research on Transformer and LSTM algorithms, achieving 5% accuracy gain.
• Optimized scalable NLP system with transformer architectures, improving language generation by 10%.
• Built stacking ensemble combining machine learning and deep learning algorithms, improving accuracy by 14% and automating predictive tool deployment.

• Leveraged machine learning to optimize operations and drive innovation across a portfolio of 8 global business units.
• Achieved $5 million cost reduction by replacing classifiers with Neural Networks, CNNs, and NLP. • Automated custom reports using Python, SQL, and Hive, reducing SLA by two days.
• Developed autoML platform, generating $12 million in incremental revenue and cost savings.
• Led research to enhance model performance, supporting a portfolio of over 60,000 models.

• Developed machine learning models for customer segmentation, increasing customer retention by 8%.
• Used MapReduce for Big Data processing and ETL, reducing M&A integration timeline by six months.
• Deployed unsupervised item coding system using fuzzy matching, generating $400,000 in additional revenue. • Built production server for intensive algorithms, reducing computational costs by 30%.
• Implemented web scraping and email content identification, reducing manual work by 75%.

Pioneered the creation of a dynamic scoring model, accompanied by insightful dashboards, to comprehensively gauge influence across prominent social networks such as Facebook, Instagram, Twitter, and LinkedIn. This inno- vative solution empowered the company to precisely identify and engage individuals with exceptional marketing potential, enhancing strategic targeting efforts.
Windows / SQL / R

• Developed predictive tools for liquid gas demand forecasting, reducing inventory costs by 15
• Created process control tool to ensure membrane fiber quality, saving $500,000 annually and increasing efficiency by 18%.
• Used stochastic modeling to optimize risk/return ratios, increasing revenue by 10% and reducing potential losses by 8%.

Demonstrated adaptability and execution prowess in spearheading internal research initiatives for the esteemed French Prudential Supervisory Authority. Pioneered the development and implementation of a novel density func- tion, reinforcing a profound grasp of intricate financial dynamics and propelling data-driven methodologies within regulatory frameworks.
Windows / SAS / Exce