The goal of this project is to apply knowledge modelling and anomaly detection techniques on structured data (e.g. processes or graphs) to efficiently flag suspicious transactions in our physical stores. This would allow to significantly improve the efficiency the efficiency of the operations, while ensuring proper authorization and review processes.

Understanding how anomaly detection can be applied to industry use cases, e.g. fraud detection, social media safety, or cybersecurity. It would be important to have experience in capturing requirements from business goals, to identify the kinds of anomalies which are more impactful in terms of business outcome.

Programming skills and knowledge of math and statistics is required.  ​

Previous experience with machine learning algorithms and data visualization techniques is highly desirable.  ​

Knowledge of anomaly detection algorithms and working with complex data structures, such as graphs, would be helpful.

Critical Thinking ⎯ Ability to analyze information objectively and make reasoned judgments.

Collaboration & Teamwork ⎯ Efficiently working with others to achieve common goals.

Communication ⎯ Capability to present ideas, data and results to teammates.