资深数据科学家 - 信用风险建模师 - Databricks
Senior Data Scientist - Credit Risk Modeler - Databricks
🚀 加入我们的远程数据产品与机器学习初创公司！ 🚀
在 Muttdata，我们构建创新的数据产品和机器学习解决方案，帮助公司解决复杂的业务挑战。作为一家快速发展的远程优先初创公司，我们对技术、协作和持续学习充满热情。
这个职位是与位于墨西哥城的领先跨国饮料公司合作的。
我们正在寻找一位高级数据科学家 - 信用风险建模师加入我们的团队 🐶🚀。你将继承、维护并改进我们的信用评分模型（命中/未命中），运用信用风险建模的专业知识，按违约概率对投资组合进行分段，并实现动态信用额度。
该职位将与数据和平台团队紧密合作，负责一个实时金融模型并负责任地进行演进。在快节奏、协作的环境中，成功需要强大的统计严谨性、对信用风险的业务理解以及责任感。
🚀 我们所做的
- 利用我们的专业知识，构建现代的机器学习系统用于需求规划和预算预测。
- 开发可扩展的数据基础设施，提升针对每个客户的高层决策能力。
- 提供全面的数据工程和定制AI解决方案，优化基于云的系统。
- 使用生成式AI，帮助电商平和零售商更快创建高质量的广告。
- 构建深度学习模型，增强各行业的视觉识别和自动化，提高产品分类、质量控制和信息检索。
- 开发推荐模型，为电商、流媒体和数字平台提供个性化用户体验，提升参与度和转化率。
🌟 我们的合作伙伴
- Amazon Web Services
- Astronomer
- Databricks
🌟 我们的价值观
- 📊 我们是数据极客
- 🤗 我们是开放的团队合作者
- 🚀 我们有主人翁精神
- 🌟 我们有积极的心态
🔍 想了解我们在做什么吗？查看我们的案例研究，深入阅读我们的博客文章，了解更多关于我们的文化和我们正在开展的令人兴奋的项目！ 🚀
职责 🤓
- 负责现有模型（树集成 / 梯度提升），重新训练并整合新特征（例如：数字支付、CISP）。
- 评估性能（AUC-ROC、F1、概率校准），并根据信用标准对风险等级 A-F 进行分段。
- 计算动态信用额度和预期损失（风险敞口），整合评分、潜力和
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🚀 Join Our Remote Data Products & Machine Learning Startup! 🚀
At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning.
This opportunity is with a leading multinational beverage company based in Mexico City.
We are looking for a Senior Data Scientist - Credit Risk Modeler to join our team 🐶🚀. You'll inherit, maintain, and evolve our Credit Score model (Hit / No Hit), applying credit-risk modeling expertise to segment the portfolio by probability of default and enable dynamic credit lines.
This role works closely with data and platform teams, taking ownership of a live financial model and evolving it responsibly. Strong statistical rigor, business understanding of credit risk, and ownership are essential to succeed in this fast-paced, collaborative environment.
🚀 What We Do
- Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
- Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
- Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
- Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
- Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
- Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.
🌟 Our Partnerships
- Amazon Web Services
- Astronomer
- Databricks
🌟 Our Values
- 📊 We are Data Nerds
- 🤗 We are Open Team Players
- 🚀 We Take Ownership
- 🌟 We Have a Positive Mindset
🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀
Responsibilities 🤓
- Take ownership of the existing model (tree ensembles / gradient boosting), retrain it, and incorporate new features (e.g., digital payments, CISP).
- Evaluate performance (AUC-ROC, F1, probability calibration) and segment risk levels A–F aligned with credit standards.
- Calculate dynamic credit lines and expected loss (risk exposure), integrating score, potential, and sales history.
- Package the model under the MFL framework (PyFunc, model_card, tests) for productionization.
Required Skills 🚀
- Proven experience in credit risk / scoring models and supervised machine learning.
- Python (scikit-learn, XGBoost), statistics, model validation, and MLflow.
- Understanding of risk metrics (PD, expected loss, exposure).
Nice to Have Skills 😉
- Experience in financial services, credit bureaus, or commercial credit portfolios.
- Experience developing AI agents / agentic infrastructure (e.g. Mosaic AI Agent Framework, agent orchestration, MCP).