
51 - 200 employees
đ Retail
Retail
Klar is a company based in Denmark that specializes in the design and sale of high-quality windows and doors. They offer a wide range of customizable products, including Dannebrog windows, Bondehus windows, and various types of doors such as terraced and facade doors. Klar provides options for both outward and inward opening windows, and they emphasize affordability by bypassing costly intermediaries. They boast up to a 12-year warranty on their products and use FSC-certified wood produced in the EU. Klar operates through a digital showroom and provides comprehensive customer service. Products are available in Denmark and neighboring countries like Norway and Sweden. Their focus on excellent service and competitive pricing is reflected in their high Trustpilot ratings from satisfied customers.
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51 - 200 employees
đ Retail
Retail
Klar is a company based in Denmark that specializes in the design and sale of high-quality windows and doors. They offer a wide range of customizable products, including Dannebrog windows, Bondehus windows, and various types of doors such as terraced and facade doors. Klar provides options for both outward and inward opening windows, and they emphasize affordability by bypassing costly intermediaries. They boast up to a 12-year warranty on their products and use FSC-certified wood produced in the EU. Klar operates through a digital showroom and provides comprehensive customer service. Products are available in Denmark and neighboring countries like Norway and Sweden. Their focus on excellent service and competitive pricing is reflected in their high Trustpilot ratings from satisfied customers.
⢠Design, build, and optimize Machine Learning models powering origination, behavioral scoring, limit management, and early-warning systems ⢠Leverage alternative data sources including transaction behavior, merchant data, and device intelligence to improve predictive performance ⢠Evaluate and implement the infrastructure required to deploy, monitor, and retrain models at scale ⢠Explore the applications of novel architectures (transformers, foundational models, etc.) for credit risk and related tasks ⢠Collaborate with cross-functional teams to identify opportunities for data-driven insights and solutions ⢠Work with other members of the Credit Risk team to build credit policies across the full customer lifecycle: origination, limit management, restructuring, and write-offs ⢠A lot of autonomy and ownership: you will own at least one Machine Learning model end-to-end ⢠Communicate findings and insights to technical and non-technical stakeholders
⢠Master's degree or above in Data Science, Computer Science, Statistics, Mathematics, or a related field ⢠5+ years of experience in Data Science, Machine Learning, or a related field ⢠Strong proficiency in Python and SQL ⢠Experience with Machine Learning libraries such as Scikit-Learn, XGBoost, TensorFlow, Keras, and Pytorch ⢠Experience owning models or analytical systems end to end, including performance monitoring, retraining, documentation, and stakeholder alignment ⢠Comfort using AI coding assistants, such as Claude Code and Codex, to improve productivity ⢠Proficiency in data analysis, visualization, and manipulation tools such as Pandas, Matplotlib, and Seaborn ⢠Optional, but a plus: Experience with credit risk, fraud, underwriting, lending, financial services, or another regulated decisioning domain ⢠Experience with dbt (Data Build Tool) to transform SQL data ⢠Experience working with novel, transformer-based architectures ⢠Strong problem-solving skills and the ability to think creatively ⢠Ability to communicate model tradeoffs, risk implications, and business impact to technical and non-technical stakeholders
⢠Competitive salary based on performance and experience ⢠Chance of earning Klar stock options ⢠26 days of paid vacation per year ⢠Computer device ⢠International work environment with amazing and highly skilled people ⢠A world class team that helps you evolve your skills in areas you're interested in ⢠Wellhub subscription to offer mental and physical health
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