Risk Control Model Engineer

Job Description

保险风险算法 | DiDi Chuxing

The Tone:
This is a full-time role at DiDi Chuxing, located in China. DiDi Chuxing is a leading global mobility technology platform dedicated to improving lives through convenient and reliable services. This critical position focuses on managing and mitigating financial insurance risks within DiDi’s ecosystem by developing and optimizing advanced algorithmic models. Your work directly contributes to the financial health and stability of our insurance offerings, impacting both our business and user experience.

The TL;DR
• Role: Full Time
• Location: In-person China
• Mission: Own the design, development, and continuous optimization of models for insurance risk scenarios to manage and improve business risk metrics.

What You’ll Actually Do
• Model Ownership: Lead the design, construction, development, implementation, and continuous optimization of models for DiDi Financial insurance risk scenarios.
• Business Accountability: Take responsibility for driving improvement in business risk indicators through effective model performance and iteration.
• Metric Translation: Deconstruct overarching business risk indicators, transform them into specific model metrics, and set clear, ambitious targets for their improvement.
• Feature Engineering: Explore various feature engineering methods, leveraging both internal and external group data to generate effective features and enhance overall model performance.
• Algorithmic Innovation: Drive advancements in data algorithms by researching and tracking industry-leading progress in artificial intelligence and deep learning, implementing new technologies in risk control.

The Must-Haves
• Background: Master’s or Ph.D. in a quantitative science or engineering field such as statistics, mathematics, physics, finance, or computer science.
• Experience: Proven capability to independently process data at a scale of tens of millions of records or more. Equivalent industry work experience is accepted in place of the academic degree.
• Skills: Familiarity with common statistical models and machine learning algorithms, including LR and GBDT, along with proficiency in general data analysis tools and algorithm optimization techniques. Strong cross-team communication skills, enabling efficient and effective information exchange with non-technical individuals to promote horizontal collaboration.