该职位来源于猎聘 Key Responsibilities:
- Lead the development and execution of data analysis projects to support fraud detection, operational monitoring, business intelligence, and performance reporting.
- Work closely with stakeholders to understand business problems, define KPIs, and deliver actionable insights and recommendations.
- Build and maintain automated dashboards and reports that support strategic and operational decision-making across teams.
- Support fraud and risk control initiatives through data analysis of transaction patterns, behavioral signals, and case investigation metrics.
- Partner with AI/ML engineers and data scientists to develop, evaluate, and deploy models that enhance automation and intelligence in business operations.
- Collaborate on the design and application of large language models (LLMs) and other AI tools to solve analytical and operational challenges.
- Drive data storytelling and visualization to clearly communicate trends, risks, and opportunities.
- Document analytical processes, KPIs, and data definitions to maintain high standards of data governance.
- Mentor junior analysts and contribute to the development of best practices in analytics, AI applications, and reporting. Key Qualifications:
- Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, or a related field.
- 5+ years of experience in data analysis or business intelligence, with exposure to risk or fraud analytics considered a plus.
- Strong SQL skills and proficiency in Python, R, or other analytical programming languages.
- Experience with business intelligence tools such as Tableau, Power BI, or QuickSight.
- Familiarity with AI/ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and understanding of LLM concepts (e.g., embeddings, prompt engineering).
- Experience leveraging AI tools (e.g., ChatGPT, Claude, LangChain) for data exploration, reporting automation, or business solution development.
- Strong communication and collaboration skills, with experience working cross-functionally.
- Ability to translate complex data findings into clear business insights.
- Organized, detail-oriented, and capable of managing multiple analytical projects. Nice to Have:
- Experience in fintech, e-commerce, or digital payments industries.
- Hands-on experience developing or implementing AI/ML or GenAI solutions in business environments.
- Experience with cloud data platforms (e.g., AWS, GCP, or Azure).