Data Scientist - Risk Analytics

Key Responsibilities

1. Conduct in-depth statistical analysis to identify patterns, trends, and anomalies within complex datasets related to risk factors and financial performance.

2. Develop and implement sophisticated predictive models to assess and quantify various types of risks, including credit risk, market risk, operational risk, and liquidity risk.

3. Collaborate with cross-functional teams to design, validate, and enhance risk models and methodologies, ensuring alignment with regulatory requirements and industry best practices.

4. Utilize advanced techniques such as machine learning algorithms, time series analysis, and Monte Carlo simulations to forecast risk exposures and assess potential impacts on business operations.

5. Perform comprehensive stress testing and scenario analysis to evaluate the resilience of risk management frameworks and identify potential vulnerabilities under adverse conditions.

6. Design and maintain scalable data pipelines for sourcing, cleaning, and aggregating large volumes of structured and unstructured data from diverse sources.

7. Communicate key findings, model insights, and actionable recommendations to senior management, stakeholders, and regulatory authorities through clear and compelling presentations and reports.

8. Stay abreast of emerging trends, methodologies, and technologies in risk analytics, data science, and financial markets to drive continuous innovation and process improvements.