Nathan Lorber

As MyUnisoft's AI referent within the Product & Technology department, I drive AI strategy, governance, and hands-on ML development for a SaaS platform serving accounting firms. • Design and develop ML classification models (XGBoost) on tabular business data, handling the full pipeline from data exploration and feature engineering through model optimisation and delivery for production integration. • Establish the company's AI governance framework for generative AI tools across the organisation. • Lead bimonthly AI workshops for both technical and non-technical audiences (up to 50 attendees), driving company-wide adoption of AI tools and best practices. • Serve as AI advisor to cross-functional teams (Product, R&D, Customer Success), providing technical feasibility assessments, solution scoping, and hands-on guidance for AI-driven features. • Maintain continuous technology watch on LLMs, generative AI APIs, and ML frameworks to inform the product AI roadmap.

• Developed a Retrieval Augmented Generation (RAG) recommendation engine utilizing GPT and NLP technologies. • Implemented an ELT pipeline using Airbyte, Snowflake, and dbt through Infrastructure as Code with Terraform. • Conducted Python codebase retro-engineering, maintenance, and expansion to enhance system performance. • Defined and implemented business KPIs to drive data-informed decision-making at majelan X.

• Conducted data exploration and cleaning using NumPy and Pandas across diverse sectors including education and health administration. • Developed machine learning models employing supervised and unsupervised algorithms with Scikit Learn, TensorFlow, and Keras. • Built APIs with FastAPI and interactive dashboards using Streamlit for enhanced data visualization and accessibility.

Tracker geometry optimization and tracking performance at the Future Circular Collider FCC International Jamboree guest speaker

Teaching math and science at middle school and high school level