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Hi, I'm Daniel G. Alfert—a quantitative and data-focused researcher with a strong mathematical foundation and hands-on backend engineering experience. I enjoy translating requirements into reliable systems and applying statistics, time-series analysis, and quantum information insights to real-world problems.\n\nCurrently pursuing an MSc in Quantum Information Science at the University of Copenhagen, I build scalable software for quantum researchers, contribute to AI/ML workflows, and thrive in collaborative, fast-paced environments. I'm excited to apply data-driven approaches to challenging problems and continue growing as a versatile engineer.…Hi, I'm Daniel G. Alfert—a quantitative and data-focused researcher with a strong mathematical foundation and hands-on backend engineering experience. I enjoy translating requirements into reliable systems and applying statistics, time-series analysis, and quantum information insights to real-world problems.\n\nCurrently pursuing an MSc in Quantum Information Science at the University of Copenhagen, I build scalable software for quantum researchers, contribute to AI/ML workflows, and thrive in collaborative, fast-paced environments. I'm excited to apply data-driven approaches to challenging problems and continue growing as a versatile engineer.

Daniel G. Alfert

Data Scientist, Full Stack Developer, Back-End Developer, +2

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Hi, I'm Daniel G. Alfert—a quantitative and data-focused researcher with a strong mathematical foundation and hands-on backend engineering experience. I enjoy translating requirements into reliable systems and applying statistics, time-series analysis, and quantum information insights to real-world problems.\n\nCurrently pursuing an MSc in Quantum Information Science at the University of Copenhagen, I build scalable software for quantum researchers, contribute to AI/ML workflows, and thrive in collaborative, fast-paced environments. I'm excited to apply data-driven approaches to challenging problems and continue growing as a versatile engineer.…Hi, I'm Daniel G. Alfert—a quantitative and data-focused researcher with a strong mathematical foundation and hands-on backend engineering experience. I enjoy translating requirements into reliable systems and applying statistics, time-series analysis, and quantum information insights to real-world problems.\n\nCurrently pursuing an MSc in Quantum Information Science at the University of Copenhagen, I build scalable software for quantum researchers, contribute to AI/ML workflows, and thrive in collaborative, fast-paced environments. I'm excited to apply data-driven approaches to challenging problems and continue growing as a versatile engineer.

Available to hire

Hi, I’m Daniel G. Alfert—a quantitative and data-focused researcher with a strong mathematical foundation and hands-on backend engineering experience. I enjoy translating requirements into reliable systems and applying statistics, time-series analysis, and quantum information insights to real-world problems.\n\nCurrently pursuing an MSc in Quantum Information Science at the University of Copenhagen, I build scalable software for quantum researchers, contribute to AI/ML workflows, and thrive in collaborative, fast-paced environments. I’m excited to apply data-driven approaches to challenging problems and continue growing as a versatile engineer.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Spanish; Castilian

Fluent

Work Experience

Software Engineer (Student) at Novo Nordisk Foundation - Quantum Computing Programme (NQCP)

June 1, 2024 - August 1, 2025

Built a greenfield internal knowledge platform for quantum researchers in a 2-person team with minimal guidance. Implemented 80% of the codebase using FastAPI for backend and Vue.js for frontend. Designed JWT-based access and refresh token flows using secure HTTP-only cookies. Developed async REST APIs and managed relational data across 15 tables. Delivered a fully functional prototype deployed on an internal machine for 50 internal users.

Applied AI Intern at Avanade

October 1, 2022 - March 1, 2023

Participated in an internal internship program focused on end-to-end deployment of computer vision models. Trained and deployed a classification model supplied via Azure ML to edge devices using Azure agents. Gained hands-on exposure to cloud-based ML workflows and production constraints.