Daouda Selim Traore

Software Engineer – AI Training | Scale AI • Designed and answered advanced technical questions on software engineering concepts, coding best practices, and debugging strategies to improve AI model training. • Wrote algorithms and reference implementations in multiple languages (JavaScript, Python, Go, Java, TypeScript, C++) to serve as benchmarks for AI-generated code. • Reviewed and evaluated AI-generated code against these implementations, ensuring correctness, efficiency, scalability, and adherence to real-world engineering standards. • Assessed code quality, maintainability, and compliance with industry best practices to enhance model reliability and practical applicability. • Delivered expert feedback on version control workflows, collaborative development practices, and advanced debugging techniques, helping refine the AI’s understanding of modern engineering workflows.

Pricefx Solutions – Design & Implementation Developed and deployed Pricefx solutions Development • System development: Design of scalable backend systems, increasing data processing capacity by 30% to support business expansion. • Backend Performance: Fine-tuned backend logic and optimized database queries, reducing response times by 20% through advanced data modeling and algorithmic improvements. • Caching Solutions: Built and rolled out caching layers, boosting data access speed and scalability by 30% across distributed environments. • Handling Large Datasets: Applied advanced data modeling and structuring techniques to ensure consistent and reliable data retrieval on high-volume datasets. • Engineering Collaboration: Maintained high code quality through proactive peer reviews, close teamwork, and rigorous testing. • Cross-team Alignment: Partnered with product managers and stakeholders to deliver backend solutions that matched both functional and business requirements.

Design and implements pricefx solutions that meet the commercial needs ** Development & Optimisation • System Architecture & Scalability: Led the design and implementation of scalable backend systems that improved overall data processing capacity by 30%, aligning with critical business growth needs. • Architecture Discussions: Actively contributed to system architecture discussions, introducing key insights that resulted in a 20% improvement in reliability and reduced technical debt. • Backend Optimization: Implemented performance tuning on backend code and database queries, reducing query response times by 25%. Enhanced system efficiency using advanced data modeling and algorithm optimization techniques. • Caching Mechanisms: Developed and implemented caching strategies, increasing data retrieval efficiency and scalability by 40% across distributed environments. • Distributed Systems: Applied advanced data modeling techniques to structure data hierarchies and ensure the efficient handling of large datasets, leading to more reliable data retrieval processes. • Collaboration and Code Reviews: Collaborated closely with engineering teams to maintain code quality through comprehensive peer code reviews and testing. • Project Collaboration: Worked cross-functionally with product managers, and stakeholders to ensure that backend solutions met the design and functional requirement ** Datamarts administration Analyze and understand transactions and commercial performance in order to propose areas for improvement of the commercial strategy. Identification of key performance indicators with client project managers and modelization of parameters Creation of the contracts datamart and the transactions datamart in order to centralize the data Analysis of the flows collected for the construction of performance indicators (turnover, volume, margin impact, product family, top customer, etc.) via Groovy script and SQL

Design of data extraction systems in job offers: Refine the search for offers on the web platform, in order to offer more precise results to users. Development of Python scripts and regular expressions for data extraction. Semantic analysis of job offers via python scripts in order to assign them categories.