Nabil Douss

EXPERIENCE

Senior Consultant

Oct 2023 - Present

EY Tax GmbH Steuerberatungsgesellschaft, Berlin

Co-engineered a Next.JS web application for processing, querying, and visualizing business transactions, enhancing data accessibility.

Co-developed and maintained a tax determination engine in C# and ASP.NET, improving data quality analysis, classification, and tax compliance for SAP business transactions.

Conceptualized and co-engineered AI-driven agents for extracting, mapping, and analyzing structured and unstructured data. These agents facilitated seamless data integration across multiple sources, empowering our clients with faster insights and more informed decision-making.

Mentored and managed a team of 3 junior consultants, fostering technical growth and team efficiency.

Consultant

Oct 2022 - Oct 2023

Ernst & Young GmbH Wirtschaftsprüfungsgesellschaft, Berlin

Optimized a backend server in JavaScript & GraphQL that processes real-time queries on transactions, while maintaining a MongoDB database.

Co-developed a Vue.js web dashboard for monitoring, filtering, and reviewing SAP business transactions.

Migrated a desktop solution to a web application using ASP.NET, optimizing backend processes including data transfer, analysis, third-party API communication, and SQL Server maintenance.

Enhanced quality assurance by implementing 80+ unit tests with XUnit, conducting code reviews, defect analysis, and corrections.

Working Student

Jun 2019 - Oct 2022

Ernst & Young GmbH Wirtschaftsprüfungsgesellschaft, Berlin

EDUCATION

Master of Science (M.S.) - Data Science & Engineering

Oct 2019 - Jun 2022

Technische Universität Berlin (Grade 1.2)

Master thesis: "Multi-domain Sentiment Analysis with an Active Learning Mechanism". The thesis proposes three model architectures for binary sentiment analysis on multi-domain textual data using an Active Learning mechanism.

Bachelor of Science (B.S.) - Computer Science

Oct 2016 - Jan 2020

Technische Universität Berlin (Grade 1.2)

Bachelor thesis: "An Analysis of Lightweight Cryptographic Algorithms".

PUBLICATIONS

ACM SAC Conference (SAC’23)

2023

Katerina Katsarou, Nabil Douss, and Kostas Stefanidis. 2023.

REFORMIST: Hierarchical Attention Networks for Multi-Domain Sentiment Classification with Active Learning. In Proceedings of ACM SAC Conference (SAC’23). ACM, New York, NY, USA, Article 4, 10 pages.