About the role
Responsibilities:
- Develop and implement statistical models, algorithms, and machine learning / deep learning techniques for fraud prevention and credit underwriting for the FinTech / Banking partners.
- Analyse large-scale datasets to identify patterns, anomalies, and trends to capture the user behaviour, including fraud, affluence, and credit risk.
- Stay up to date on the latest fraud trends and technologies to proactively identify vulnerabilities and enhance fraud prevention strategies.
- Design experiments to evaluate and optimise the performance of existing AI models and algorithms.
- Own the end-to-end data pipeline, including data analysis, data processing, building the AI models, and monitoring of already deployed models.
Requirements:
- Bachelor's degree or higher in Applied Mathematics, Statistics, Computer Science, or a related field.
- 5+ years of experience in Data Science and working in fintech startups or financial services-based companies is preferred.
- Strong expertise in different AI verticals, including machine learning, statistical methods, deep learning, computer vision, and NLP.
- Excellent communication and collaboration skills, with the ability to work effectively in a team environment.