Python, Django, PostgreSQL, ElasticSearch, RabbitMQ, Heroku

Ruby, React

Lead Developer (Senior Full Stack Developer) at Lighthouse SE.

Blocket has a new feature that enables users to sell their vehicles to the highest bidding car dealership. Christoffer was requested to develop a landing page for this option. He was able to deliver the requested page ahead of time and therefore was handed additional tasks.* Work on the car valuation page * Create new funnel for selling cars on Blocket.* Optimize for SEO, Implement Contentful CMS and Add tracking (Datadog, GA, GTM, Blocket PULSE)Next.js, React, AWS, Docker, Docker-compose, Kubernetes, Contentful, JavaScript, Django, Python, SEO, Tracking, Travis CI, Spinnaker, Styled Components, Github, Google Tag Manager, Google Analytics, Blocket PULSE tracking tool, Datadog, K9s, kubectx, saml2aws, Spinnaker, Jira, Figma, CSS, UI, UX, HTML, Node.js, npm, api, vscode, linux, windows, ssh, responsive design, Slack api, MicroservicesFrontend development, Backend development, Cloud, CI/CD, Full stack development

Christoffer joined Project 3D (Data-Driven Development) to work on projects delivering data-driven solutions, models, and applications for the company. The two main projects involved the development of applications capable of providing farmers with fertilizer strategies for their crops and provide farmers within the milking industry with statistics and evaluations of milk production. Python, Pandas, PySpark, Databricks, Seaborn, SQL, Docker, Docker compose, Azure data lake storage, Azure app service, Azure keyvault, Azure container registry, Django, Azure functions, Azure data factory, PostgreSQL, ETL, Django REST Framework, Azure DevOps, Azure SQL Server, Azure SQL Database, Angular, Swagger, Auth0, PandasSchema, CeleryBackend development, Frontend development, Data engineering, CI/CD, Full stack development, Data Science, Cloud, Machine learning

Scania is a major Swedish manufacturer of commercial vehicles, specifically heavy trucks and buses. Smart Engineering Lab (SEL) is a lab within R&D focusing on accelerating projects or investigating the applicability of new technologies. Christoffer joined the lab as a full stack developer with machine learning expertise. In the initial project, he developed a VR application in Unity which gave rise to several other projects and prolonging his contract. * Machine learning - Exploring the possibility to classify whether error codes were generated by real faults or during maintenance of the vehicle.* Machine learning - Development of a system capable of providing mechanics with solutions to problems encountered at the workshop with the help of natural language processing* Data visualization - Application capable of visualizing the assembly options of parts for vehicles. * Virtual Reality - Virtual prototyping tool for parts in order to reduce initial prototype cost, increase prototyping speed, and reduce error.Natural Language Processing, Machine Learning, Python, Scikit-learn, TPOT, Pandas, Jupyter Notebooks, AWS Elasticsearch, AWS Comprehend, Visual Studio Code, Angular, React, Flask, Unity, C#, Real-time networking, Photon PUN 2, Virtual Reality, HTC Vive Pro, Visual Studio, Django, React, Flask, MongoDB, NPM, VisJS, TypeScript, JavaScript, HTML, SCSS, GV Design sprint, Syncfusion, Git, Visual Studio Code, Windows, Linux, Node.jsTech lead, Team lead, Frontend Developer, Backend Developer, Data Scientist, Full stack Developer, Machine learning engineer, Cloud, CI/CD

Teknomedia is a production company for digital media (news) and belongs to the NTM-concern which is one of Sweden's biggest media concerns. They had a tagging system for articles which was in need of improvements. Teknomedia wanted to investigate whether they can improve the quality of tags and create structure in the system with the help of natural language processing, integrated with a fresh web application.TF-IDF, Vector Space Models, Angular 2, Angular 4, Angular 5, Node, Bootstrap, ASP.NET Web API 2, C#, HTML, CSS, Typescript, Font Awesome, SQL, R, Python, Regex, Postman, Git, nltk, scikit-learn, SQLData Scientist, Frontend developer, Backend developer, Full stack developer, Machine Learning, Natural Language Processing, Web development

Siemens Industrial Turbomachinery AB (SIT AB) manufacture powerplants and turbines with high efficiency and low emission rates. Gas turbines manufactured by SIT AB consist of many parts with different maintenance cycles and lifetime expectancies. Determining the condition of parts is hard and for safety purposes, a quite large safety margin is added to mediate the issues. Siemens wanted to investigate whether the condition of parts can be estimated in a better way.HTML, CSS, Google Chart Tools, JavaScriptFrontend developer, Data analyst, Web development, Machine learning