Quantitative Risk Data Scientist, Fintech

About the role

Design and implement algorithmic solutions and predictive models to optimize revenue, assess credit risk, and support portfolio risk management for microloans and other financial products. Analyze large datasets, develop and refine risk assessment tools and methodologies, and collaborate with data scientists, traders, and data and machine-learning engineers. A bachelor's or master's degree in data science, statistics, finance, mathematics, or a related field is required, along with 2–5 years of relevant quantitative risk analysis experience, preferably in financial services. Candidates should have strong statistical and machine-learning modeling skills, proficiency in Python or R and big-data risk analytics, experience building portfolio risk assessment tools, and familiarity with secure coding practices such as OWASP or NIST.