[HN] Research Assistant (8 Months & Contracted Through 3rd Party)

About Project
Our research project involves Anomaly Detection in blockchain data and Machine Learning model development. We will address the following research questions:
1. What approaches can be taken to improve data collection techniques and bolster labelled data for supervised learning in cryptocurrencies?
2. How does the imbalance between normal and anomalous transactions affect the performance of anomaly detection models?
3. What Machine Learning strategies can be employed to mitigate this issue for high-Volume, low-Variety data?
We are seeking a highly skilled and motivated Research Assistant who is a Data & Artificial Intelligence (AI)/Machine Learning (ML) Specialist to contribute to a cutting-edge research project focused on identifying fraudulent transactions in public blockchains. The successful candidate will be responsible for creating a Data Pipeline, and classifying ML solutions to test and enhance anomaly detection in blockchain data.
Reports to: Chief Investigator
Indirectly reports to: Office of Research and Innovation
Key Accountabilities
Conduct desktop research regarding blockchain data pipelining, and AI/ML anomaly detection techniques.
Research, design, integrate and implement appropriate solutions to test anomaly detection.
Analyse, design, develop, implement, and test algorithms and AI-ML models.
Collaborate with the research team to identify innovative approaches for the problem.