Deloitte Audit & Assurance - Clustering and Anomaly Detection Intern (Summer 2021/Fall 2021) in New York, New York
Our audits are fueled by more than just technology - what really sets us apart are our insightful professionals, collaborative culture, and commitment to innovation and continuous improvement. Our audit professionals apply a streamlined, intelligent approach to the audit, enabled by innovative tools and technologies. Quality is our top priority, and by focusing on innovation, we continue to raise the bar on quality and deliver greater value to our clients. Learn more about Deloitte Audit.
The Audit Transformation team is seeking highly motivated PhD 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.
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 ability to explain any outcomes/results.
Collaborate with colleagues to implement reusable, efficient and maintainable software components using mainstream programming languages.
Incubate innovative concepts and develop publications.
A successful intern will have the following:
Outstanding collaboration, interpersonal and communication (verbal & written) skills in English is 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.
Current student in a PhD program in a quantitative field (computational linguistics, computer science, engineering, mathematics, physics, machine learning, 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.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.