Risk Analyst

As a Risk Analyst at PayJoy, you will be responsible for extracting and analyzing data to drive policy recommendations and dashboard creation focused on optimizing risk outcomes across credit product portfolios. You’ll utilize SQL and R or Python, making data-driven recommendations that enhance product profitability and risk KPIs, working collaboratively with the Data Science team to implement advanced machine learning and AI models.

To qualify for the Risk Analyst position at PayJoy, you should have a Bachelor's degree in Finance, Economics, Mathematics, or a related quantitative field, alongside at least 2 years of experience in a rigorous analytical role. Proficiency in SQL, Python, and a solid understanding of statistical tools and large datasets are crucial, while experience in consumer finance is a plus.

The Risk Analyst role at PayJoy is pivotal to our mission by using data analysis to ensure our financial products are accessible and profitable for underserved markets. Your insights will directly influence how we approach risk, thereby allowing us to better serve our customers and expand the financial options available to them, aligning perfectly with our goal of helping the next billion.

In your role as a Risk Analyst at PayJoy, you'll primarily employ SQL and either R or Python to manipulate and analyze data. You will also collaborate closely with our Data Science team to leverage machine learning and AI technologies, creating dashboards to assess credit portfolio performance and supporting continuous improvement efforts.

PayJoy offers an array of benefits for its Risk Analysts, including 100% company-funded health and dental insurance for employees and their immediate family, annual perks for professional development and co-working travel, in addition to remote work support through equipment and wellness perks, all contributing to a balanced work-life environment.

Be sure to highlight your familiarity with SQL, R, or Python, providing specific examples of projects where you utilized these tools to manipulate or analyze data. Discuss any trends you've identified in your analysis and how your efforts influenced decision-making.

Share your process for identifying key performance indicators (KPIs) relevant to the credit portfolios. Discuss how you gather data, choose visualization types for clarity, and ensure that your dashboards inform actionable business decisions, potentially including your experience with tools like Tableau or Power BI.

Provide a detailed example, focusing on the analytical steps you took to arrive at your recommendation, the data you analyzed, and the positive impact it had on the project or organization. Emphasize how your analytical skills directly led to improved risk management.

Mention specific resources, such as industry publications, online courses, or conferences, that you utilize to keep up with trends and best practices in risk analysis. Share how integrating this knowledge into your work has helped you overcome challenges or propose innovative solutions.

Discuss how machine learning techniques can enhance risk assessment, including examples of models you've worked with. Describe how these techniques help in predicting customer behavior, optimizing portfolios, and reducing financial risks, showcasing your grasp of current methodologies.

Illustrate your experience handling large data sets by detailing the tools you used to analyze and interpret complex data. Describe the challenges you faced and how you overcame them, ensuring you paint a picture of your strong analytical capabilities.

Talk about your time management strategies, such as using project management tools, setting clear deadlines, and prioritizing tasks based on their impact on the business. Give an example of a time when effective prioritization led to successful project completion.

Share your collaborative strategies, emphasizing the importance of open communication and mutual respect. Provide an example of how you've successfully collaborated with team members from different backgrounds to achieve a common goal in a project.

Discuss specific challenges, whether they be related to data integrity, stakeholder communication, or changing market conditions. Describe your problem-solving approach and any adaptations you made to improve outcomes.

Highlight the importance of clear, jargon-free communication when presenting your findings to stakeholders. Discuss how you would tailor your explanations, utilize visual aids, and ensure that they understand the implications of your recommendations.