Data Scientist - Portfolio ManagementCÔNG TY CỔ PHẦN TRUSTING SOCIAL - AI Fintech Trusting Social

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.
Developing and implementing credit risk models and analytical tools to assess portfolio performance, credit risk, and profitability.
Analyzing and interpreting data to identify trends, patterns, and insights that drive portfolio management decisions.
Conducting ad-hoc analysis and data mining to support portfolio optimization and strategy development.
Collaborating with business stakeholders to understand their needs and requirements, and to develop and implement solutions that meet their needs.
Creating and maintaining reports and dashboards that provide insights into portfolio performance and key performance indicators (KPIs).
Designing and conducting A/B tests to evaluate the impact of new portfolio strategies and tactics.
Maintaining up-to-date knowledge of industry trends, best practices, and regulatory requirements related to credit card portfolio management.
Communicating complex analytical findings and recommendations to non-technical stakeholders, including senior management.
Mentoring and coaching junior analysts and data scientists on the team.
Partnering with data engineers and other technical teams to ensure data quality, availability, and scalability.
Conducting competitive research to stay informed of market trends, customer preferences, and emerging technologies that may impact the credit card portfolio.
Perform highly complex activities related to financial products, business analysis, and build dashboards for portfolio monitoring.
Utilize statistical and machine learning techniques to identify patterns and trends in financial data
Develop and implement data-driven investment strategies that optimize portfolio performance