We are seeking a Stockholm-based Master’s student in Mathematics, Finance, CS, or Data Science to undertake a degree project focused on enhancing our fraud detection and prevention system. The goal is to identify and prevent fraudulent activities in tenant applications and rental transactions. These activities may include false information submissions, identity theft, fraudulent payment methods, or collusion with property owners. This project will involve building and testing models/algorithms to detect fraud patterns, creating a real-time detection system, and developing automated alerts and prevention strategies. The successful candidate will work at our office during the Spring semester, collaborating closely with our data science, product, and development teams.

What you can expect from us

Writing a master thesis is fun but for many the last thing they do before graduating. We want you to have a suitable scope and technical support to be able to write and finish your degree.

🎓 Previous Master’s Theses

At Qasa, we’ve had a strong history of collaborating with Master’s students on impactful projects. Here are some of the recent theses completed at Qasa:

• Automated Home Review: Eric Dahlgren developed a system to review home ads before they are published. Using XGBoost and SHAP, an interpretable anomaly detection model was built to automate ad reviews. The model not only scores ads but also provides human-readable explanations to assist decision-making. You can read the thesis here: Enhancement of an Ad Reviewal Process through Interpretable Anomaly Detecting Machine Learning Models
• Rent Prediction: Vasigaran Senthilkumar focused on improving house rental price predictions by incorporating external features such as walk scores and interest rates. The work also introduced methods for handling uncertainty in predictions, including generating prediction intervals and managing uncertain rent data to enhance model adaptability and generalization. You can read the thesis here: Enhancing House Rental Price Prediction Models for the Swedish Market
• Recommendation Systems: Julia Byström created and A/B tested (in production!) two new algorithms to improve tenant rankings for landlords in our “Find tenant” feature. The algorithms were rigorously tested and deployed in production, contributing significantly to our recommendation systems. You can read the thesis here: Probabilistic Weighting and Deferred Acceptance in Reciprocal Recommendations.

What You’ll work on

• Research, develop, and prototype fraud detection algorithms/models using supervised and unsupervised learning.
• Tackle complex problems related to feature engineering for fraud detection.
• Collaborate with the product and development teams to integrate fraud detection models into our platform.
• (stretch) Build a real-time fraud detection pipeline to seamlessly identify suspicious activities.
• (stretch) Create an automated alert system to help us prevent and respond to fraud in real-time.
• Gain hands-on experience in anomaly detection, risk management, and real-time data processing.
• Communicate your research findings, progress, and final results to both technical and non-technical stakeholders.

You could be a great fit if you

• Are experienced or interested in learning Python, Ruby on Rails, PostgreSQL, and familiar with the AWS ecosystem or related programming languages/services.
• Have hands-on experience with machine learning libraries such as scikit-learn, TensorFlow, and PyTorch.
• Enjoy working with graph databases and exploring new approaches to solving fraud-related problems.
• Excel at applying theoretical and empirical research to solve practical challenges.
• Are passionate about data-driven decision-making, cybersecurity, and solving real-world problems.
• Can communicate complex research clearly, precisely, and in an actionable way.

What we offer

• An opportunity to work on a high-impact project addressing real-world challenges in the long-term rental market.
• Mentorship and guidance from experienced data scientists, developers, and product experts.
• A collaborative, innovative, and fun working environment.
• Potential future employment opportunities at Qasa.