Clustering & Anomaly Detection Intern

Job Description

The Audit Transformation team is seeking highly motivated Ph.D. students available for 3 to 6-month internships in the area of clustering and anomaly detection. The successful candidates will work with the other data scientists on the team to develop solutions to real-world problems. You will have the opportunity to test your knowledge in a challenging problem-solving environment. You will be encouraged to think outside the box, innovate, and find novel solutions to some of the most challenging problems within our business.

Responsibilities

• Utilize machine learning techniques to develop tools (such as clustering, anomaly detection, and time-series analysis) for analyzing large data sets consisting of transactional data with a focus on the ability to explain any outcomes or results.
• Collaborate with colleagues to implement reusable, efficient, and maintainable software components using mainstream programming languages.
• Incubate innovative concepts and develop publications.

Preferred Skills

• Outstanding collaboration, interpersonal, and communication (verbal & written) skills in English are required.
• Drive and motivation for career development and open to taking on challenges.
• Team player who can also be independent, prioritize work and thrives in a fast-paced dynamic environment.

Qualifications

• Current student in a Ph.D. program in a quantitative field such as Computational Linguistics, Computer Science, Engineering, Mathematics, Physics, Machine Learning, and Statistics.
• Experience with clustering, anomaly detection, dimension reduction, neural networks, etc.
• Proficient in Python with software development experience.
• Experience with deep learning tools such as Theano, PyTorch, Tensorflow, etc.
• Publication and research experience in related fields.
• The start date for this position will be in Summer/Fall 2022 or Winter 2023.