Data Scientist - Portfolio Management

Trusting Social

Tp Hồ Chí Minh
Lâu dài
Toàn thời gian

1 tháng trước
Ứng tuyển Dễ dàng

Making Financial Inclusion a Reality using Machine Learning and AIWe advance data science and technology to bring financial inclusion for all, on a scale never before possible. In just two years, Trusting Social has become the biggest and fastest-growing credit scoring platform and B2B2C loan marketplace in Southeast Asia, with more than 50% of new to bank personal loans in Vietnam going through us. We are on a trajectory to score a billion people, with our platform launching in other Asian countries including Indonesia and India. Funded by Sequoia Capital, we have been profitable since 3 months after first launch in Vietnam. Headquartered in Singapore, our teams are distributed among Ho Chi Minh, Melbourne, Jakarta, Manila, Bangalore, and Mumbai.The company is led by a dynamic group of seasoned entrepreneurs, technologists and scientists seeking to disrupt the lending space and democratize access to capital for billions of underserved consumers.ResponsibilitiesThe 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

Requirements

Post Graduate degree (Masters or Ph.D.) in Quantitative field such as Statistics, Mathematics, Computer Science, Economics, or equivalent experience preferred
3 to 5 years of professional working experience in applying statistical and ML solutions to business problems
Strong knowledge and hands-on experience on machine learning, or statistics and experimentation
Results oriented with strong analytical and problem solving skills
Good business acumen with strong ability to solve business problems through data driven quantitative methodologies
The ability to communicate results clearly to technical and non-technical audiences
Demonstrated ability to research and innovate solutions to solve business problems
Experience in bank related products such as unsecured personal loans and credit card is preferred

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