Trusting Social

Tóm tắt công việc

The Credit Insight team consists of highly skilled and passionate data scientists who are committed to staying current with the latest advancements in data science, machine learning, and artificial intelligence. Our team tackles a wide range of areas including credit scoring, fraudulent activity detection, profit optimization, and developing advanced technologies such as automatic speech recognition (ASR), large language models (LLM), and text-to-speech (TTS) to facilitate voice communication with customers. By analyzing extensive datasets that capture daily customer behavior, we continuously uncover unique and intriguing machine learning and business challenges. Our goal is to build robust machine learning models that enhance user experience and optimize the profitability of our financial products.

Responsibilities

• Train and Fine-tune LLM Models: Develop and refine large language models to follow instructions, comprehend customer inquiries, and communicate naturally and effectively.
• Design and Develop LLM Agents: Create and tailor LLM agents to meet specific business needs and objectives.
• Build Evaluation Frameworks: Establish comprehensive evaluation frameworks to assess the performance and effectiveness of LLM agents.
• Feedback Collection and Model Improvement: Develop systems for collecting user feedback and iteratively improving model performance based on this feedback.
• Develop Other ML Models: Design and implement various types of machine learning models to address diverse business needs.
• Collaboration and Consultation: Work closely with peers, colleagues, and managers to resolve issues and achieve shared goals.
• Develop other ML models. 

• Post Graduate degree (Masters  or Ph.D.) in Quantitative field such as Statistics, Mathematics, Computer  Science, Economics, or equivalent experience preferred 
• 3 to 6 years of professional working experience in applying applying statistical and ML solutions to business problems 
• Strong proficiency in programming languages such as Python, R, or Java.
• 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