Description:

As a Sr. Risk Data Analyst, you will be a vital part of our 2nd line risk team and serve as the go-to expert for transforming raw data into actionable intelligence.
You will dive into vast datasets, utilizing your SQL, Python, and Tableau mastery to extract meaningful insights across all areas of risk, including credit, operational, and compliance.
You will apply your deep understanding of statistical modeling and machine learning to solve complex risk challenges.
You will craft compelling visualizations and presentations that communicate complex risk findings to both technical and non-technical audiences, influencing key decision-making.
You will identify emerging risks and trends before they become headlines and develop early warning indicators and predictive models to mitigate potential threats proactively.
You will collaborate with risk managers and business partners to continuously enhance our risk reporting, analysis, and monitoring frameworks.
You will engage in diverse projects, learn new tools and techniques, and continuously expand your risk management expertise.

Requirements:

You must have experience in SQL, Python, and Tableau.
Proven experience in statistical modeling and machine learning applications is required.
A strong understanding and practical experience with statistical concepts and building predictive models is necessary.
You should have demonstrated experience in applying data science methodologies to real-world problems.
Experience within the banking industry is a plus.
Experience working with Git is also a plus.
You must be able to effectively communicate complex ideas to both technical and non-technical audiences through presentations and data visualizations.
You should be highly motivated and thrive in a fast-paced, dynamic environment.
Taking initiative, asking questions, and being eager to learn are essential traits.
You should embrace challenges as opportunities for growth and be passionate about working with others to achieve common goals.
A Bachelor's degree in Mathematics, Physics, Statistics, Computer Science, Engineering, Economics, or a similar quantitative field, or equivalent practical experience is preferred.

The salary range for this role is $105,000 - $135,000 per year, based on function, level, and geographic location.
Final offer amounts are determined by multiple factors, including candidate experience and expertise, and may vary from the identified range.