Jonas Johansen

Iceland's leading AI firm, DataLab - a subsidiary of Origo, provides AI and data solutions to its customers. Worked on numerous projects in data modeling, data engineering, data science, prediction modeling, automation and generative AI, in addition to product development for Datalab's agentic LLM product Ari - with module-based integrations to databases, graphs and more.

• Developed IaC & CI/CD automation setup in Azure for DataLab's generative AI product Ari.
• Project Manager & ML Engineer for Ari at Nordic Visitor (NV) - built a customized agentic LLM software solution that reduces time spent on customer enquiries by ~80%. Built integrations to SharePoint, Asana, Microsoft Word and NV's own APIs and website. Rolled out for 50+ employees in Iceland, Scotland, Sweden and Germany.
• Project Manager & ML Engineer for Ari at Origo - built an LLM RAG agent that allows Origo's employees to interact with their employee handbook through an LLM chat interface. Rolled out for all 300+ Origo employees.
• Data & ML Engineer for churn prediction at Nova Iceland - built a churn prediction model for Nova's telecom subscribers using Azure ML Studio. Utilized models such as xgboost, random forest & logistic regression. Wrote report on findings. Presented results and implications for the BofD at Nova.
• Worked on various projects in DE, DS & GenAI for the City of Reykjavik, Ministry of the Environment, Energy and Climate, Arion Bank and more.

Recruited by manager at Vygruppen AS. Stationed from beginning at the Payment Solutions team at Norwegian Air Shuttle ASA - a Norweigan low-cost airline. Project related to building an analytics solution for transactional data. Tools mainly native AWS including AWS S3, AWS Lambda, AWS Glue, AWS Redshift, AWS QuickSight and more. IaC with CloudFormation. Scrum-based project structure.

• Built batch and real-time processing data pipelines handling thousands of transactions per day converting raw data from S3 into structured tables in Redshift using AWS Glue (PySpark) and AWS Lambda (Python).
• Had weekly presentations on progress, analyses and cost optimizations for the management.
• Worked together with the central analytics team and other departments at Norwegian to ensure and enable smooth data sharing across the organization.
• Tech Lead for Aboveit's 7-person analytics divison with responsibility for team's technical quality and development.
• Built and demonstrated Microsoft Fabric solution for analyzing the stock market utilizing NLP on annual reports in combination with quantitative data from Börsdata internally at Aboveit.

Part of Visma bWise's market-leading Graduate Program. Stationed entire time at Vygruppen AS - one of Norway's biggest public transportation companies. Project related to big data handling of sensor data from buses mainly utilizing AWS S3, AWS Lambda, AWS Redshift, Databricks, Qlik Sense and SnapLogic. IaC with Terraform. Agile project structure.

• Constructed batch (PySpark) and real-time (pandas) processing pipelines successfully handling a total of more than 30 million rows of semi-structured data per day.
• Designed 20+ schemas in AWS Redshift related to passenger counts, positional data, screen messages, sales records and much more.
• Created and designed 12 dashboards for daily or real-time use for Vy Buss management.
• Developed a notification system utilizing AWS S3, AWS SNS and AWS Lambda notifying technical failures related to system logins potentially saving ~50 000 NOK per notification.

Two-month internship in a startup located at StartupLab Oslo. Responsible for all financials (cash flow statements, balance sheets and financial planning), presented this to potential investors and business partners. Sales and investment strategy. Solved vehicle routing problems in R utilizing Google's Distance Matrix API. Participated in the workshop Fundraising for Startups from Startup Norway.

Analytics heavy curriculum with courses covering decision modeling, statistics, machine learning, advanced textual data analysis as well as finance and more. The Business Analytics profile focuses on the application of analytical tools such as Python, R, Tableau, AMPL, SQL, Anaconda, Keras and Tensorflow.

Good academic perfomance, with a GPA of 4.4/5.0 at master's level. Achieved the top grade on the master's thesis, "The Use of Textual Data Analysis and Machine Learning in Bankruptcy Prediction", which was nominated for the Lehmkuhl Grant at NHH for most innovative thesis.

Went to the University of Melbourne for an exchange semester during the bachelor's program.

6-week long experiential entrepreneurship programme for students, with a primary focus on rapid market validation of ideas, assumption testing, product/service development, growth hacking, cultivating an entrepreneurial mindset, practical application of digital tools, raising capital and so forth.

The selected participants go through the entire process of bringing a new product/service to market, and learn to use modern innovation frameworks and methods in practice, ranging from LEAN startup to design thinking, Jobs to Be Done, agile and customer development.