Data Scientist - Portfolio Management

For credit card portfolio management, our mission is to optimize credit line management, credit limit setting, and collections. We utilize our expertise in data science to develop predictive models and analytics that forecast customer behavior and credit risk. Additionally, we leverage machine learning and AI techniques to identify patterns and insights in transaction data, customer behavior, and marketing campaigns. By collaborating with other teams, such as product development, marketing, and customer service, we aim to deliver a seamless and personalized customer experience across all touch points. Ultimately, our goal is to minimize risk and optimize portfolio performance metrics for the benefit of our customers.
Responsibilities
The ideal candidate will have a passion for utilizing data and analytics to optimize portfolio performance. The successful candidate will be responsible for analyzing large datasets, developing predictive models, and generating actionable insights for credit card portfolio management.
Maintaining up- to- date knowledge of industry trends, best practices, and regulatory requirements related to credit card portfolio management.
Collaborating with business stakeholders to understand their needs and requirements, and to develop and implement solutions that meet their needs.
Partnering with data engineers and other technical teams to ensure data quality, availability, and scalability.
Conducting ad- hoc analysis and data mining to support portfolio optimization and strategy development.
Communicating complex analytical findings and recommendations to non- technical stakeholders, including senior management.
Develop and implement data- driven investment strategies that optimize portfolio performance
Utilize statistical and machine learning techniques to identify patterns and trends in financial data
Perform highly complex activities related to financial products, business analysis, and build dashboards for portfolio monitoring.
Analyzing and interpreting data to identify trends, patterns, and insights that drive portfolio management decisions.
Designing and conducting A/B tests to evaluate the impact of new portfolio strategies and tactics.
Conducting competitive research to stay informed of market trends, customer preferences, and emerging technologies that may impact the credit card portfolio.
Creating and maintaining reports and dashboards that provide insights into portfolio performance and key performance indicators (KPIs).
Mentoring and coaching junior analysts and data scientists on the team.
Developing and implementing credit risk models and analytical tools to assess portfolio performance, credit risk, and profitability.