Sven Bokn

AI Architect & Data Engineer

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About

I am a Full-Stack Builder who bridges the gap between advanced analytics and production-grade software. Unlike pure data scientists who often stay in prototyping environments, I design and deploy robust, end-to-end systems.

With a strong foundation in mathematics (M.Sc.) and deep engineering experience, I build architectures that are scalable, secure, and ready for the real world.

Services & Expertise

I help organizations build and implement production-ready AI solutions. My core focus areas are:

Predictive Modeling & Data Science
Designing statistical models and valuation engines that solve real business problems. From data pipeline engineering to MLOps deployment.

Internal AI & RAG Architecture
Building secure "Chat with your Data" systems using Vector Databases and LLMs. I handle the full stack from data ingestion to user interface.

Autonomous Agents & Automation
Developing intelligent agents that automate complex workflows, web scraping, and data enrichment.

Core Skills

AI & Machine Learning

LLMs RAG Vector Databases Generative AI Computer Vision TTS/STT Technologies NLP Deep Learning ML Algorithms Model Optimization

Development & Cloud

Python Azure AWS GCP REST APIs Data Pipelines Microservices CI/CD Serverless Computing

Data Science

Data Analysis Data Visualization Statistical Modeling Time Series Analysis Big Data Processing A/B Testing

Timeline

2023 - Present

Senaible - Founder & AI Architect
Operating as an independent AI consultancy delivering production-grade solutions. Specializing in autonomous agents, data engineering, and predictive modeling for clients and internal ventures. Key Products: Omegn (Generative AI Platform) and CoWorker (RAG System).

2021 - 2023

Hjemla - Core Data Scientist
Engineered the machine learning models driving Norway's leading Automated Valuation Model (AVM). Built scalable ETL pipelines on AWS and implemented MLOps practices for real-time property valuation.

2020 - 2021

TietoEVRY, Financial Services - Data Scientist & AI Advisor
Led the AI development for a Personal Finance Management (PFM) solution for banking clients. Built deep learning models for transaction categorization and advised banks on AI strategy.

2019 - 2020

University of Bergen - Topics in Statistics and Machine Learning
Selected coursework in statistics and machine learning to build practical data science skills. Self-directed study bridging pure mathematics background with applied computational methods. Developed foundation for career shift into AI and data science.

2019

University of Trento - 11th School on Analysis and Geometry in Metric Spaces
Participated in advanced research workshop on geometric measure theory in Carnot-Caratheodory groups. Engaged with cutting-edge concepts in metric spaces with applications to degenerate elliptic equations, optimal control theory, and differential geometry. Collaborated with international researchers on current developments in the field.

2018 - 2019

University of Bergen - Teaching Assistant
Served as teaching assistant for MAT235 - Vector and Tensor Analysis while simultaneously enrolled as a student in this challenging postgraduate course. Prepared teaching materials, held lectures, and evaluated student assignments and midterm exams. Guided fellow students through complex mathematical concepts and problem-solving techniques.

2018

The Fields Institute - Connections Between Complex, Harmonic, and Stochastic Analysis
Selected to participate in international workshop connecting researchers from Norway and Canada. Explored interdisciplinary connections between Stochastic Analysis, Harmonic Analysis, Geometric Function Theory, Mathematical Physics, and Geometry. Developed deeper understanding of cross-disciplinary mathematical applications.

2017 - 2019

University of Bergen - Master's in Pure Mathematics
Completed Master's degree in Pure Mathematics with focus on Mathematical Analysis and Differential Geometry. Developed strong foundation in advanced mathematical concepts including functional analysis, differential geometry, and measure theory.

Final thesis received grade A.

2017

UC Berkeley - Topics in Pure Mathematics
Exchange program studying Number Theory, Differential Geometry, and Fourier Analysis (Signal Processing). Gained international academic perspective at a world-leading institution.

2014 - 2017

University of Bergen - Bachelor's in Mathematics
Completed Bachelor's degree in Mathematics with comprehensive foundation in mathematical principles and theories. Developed skills in scientific writing and mathematical analysis. Coursework included complex analysis, real analysis, algebra, and linear algebra.

Final thesis received grade A.

Highlighted Projects

2023 - Present

Omegn - Generative AI Platform

Client: Senaible (In-house Product)
Role: Lead Architect & Product Manager

Built a multi-modal content platform that transforms raw data into immersive audio experiences. The system utilizes LLMs to transform source material into engaging narratives and Neural TTS to synthesize studio-quality audio.

Tech: Python, Azure, Generative AI, PWA, Neural TTS.

Impact: Reduced content production time by ~90% through AI automation, enabling rapid deployment for cultural institutions.

2021 - 2023

Automated Property Valuation Engine (AVM)

Client: Hjemla
Role: Core Data Scientist

Engineered and optimized the core valuation models used to price residential properties across the entire Norwegian market. Built robust ETL pipelines on AWS to process large-scale real estate datasets.

Tech: Python, AWS, Gradient Boosting (CatBoost/LGBM), MLOps, PostgreSQL.

Impact: Solved critical data quality issues programmatically, directly improving the reliability of valuations used by consumers and banks.

2020 - 2021

AI-driven Personal Finance (PFM)

Client: TietoEVRY (Financial Services)
Role: Data Scientist & AI Advisor

Led the data science development for a transaction categorization engine used in digital banking. Designed deep learning models (TensorFlow) to analyze spending patterns and advised banking partners on AI strategy.

Tech: Python, TensorFlow, Keras, Financial Data Analysis.

Impact: Delivered a validated PoC demonstrating how AI could automate transaction sorting for millions of bank customers.

Media

The Unconventional Path to AI Innovation

Discover how Sven Bokn’s unique background led him to found Senaible. Read his perspectives on resilience, taking calculated risks, and why an unconventional career path is an asset in modern tech development.

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The Mathematical Foundation of Problem Solving

Explore how Sven applies mathematical rigor to real-world chaos. Learn why the persistence required in pure mathematics is the perfect training ground for solving complex data engineering challenges and building robust AI systems.

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