6 часов назад
Senior Data Scientist (Fraud Detection)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Scientist (Fraud Detection) (Machine Learning/Fintech): Building and improving machine learning solutions for lending and payments products with an accent on fraud detection, feature engineering, and production model ownership. Focus on detecting coordinated fraudulent behavior, developing real-time rule-based and ML decisioning systems, and monitoring model performance across the product lifecycle.
Location: Guadalajara, Mexico
Company
is a Latin American fintech company building buy now, pay later and online consumer credit products for customers in Mexico.
What you will do
- Build and improve lending and payments products using machine learning and data analytics.
- Own production ML models end to end, including experimentation, feature development, monitoring, anomaly analysis, and continuous improvement.
- Develop reliable, well-documented ML pipelines using open-source technologies and cloud-based tools.
- Partner with Product, Engineering, Risk, and Business teams to deliver product enhancements and define ML-related engineering requirements.
- Use AI-enabled tools and emerging AI capabilities to accelerate analysis, experimentation, and model development.
- Mentor team members, contribute to code reviews and testing practices, and support technical recruiting when needed.
Requirements
- Quantitative background in Engineering, Physics, Mathematics, or equivalent practical experience.
- Advanced machine learning knowledge and hands-on experience applying ML in academic or industry settings.
- Strong Python, ML libraries, SQL, and Unix-like environment experience.
- Experience using AI-powered tools and emerging AI technologies in data science workflows, experimentation, analysis, or product solutions.
- Strong analytical and communication skills, including the ability to explain complex topics to technical and non-technical audiences.
- Fluency in English is required.
Nice to have
- Experience with organized fraud detection using graph analytics, network science, device fingerprinting, or behavioral biometrics.
- Experience with hybrid rule-based and ML systems for real-time decisioning.
- Knowledge of AML and KYC regulatory frameworks and their application to fraud detection.
- Experience with AWS machine learning services and causal inference techniques such as uplift modeling or treatment effect estimation.
- Background in Risk, Economics, Econometrics, Finance, pricing, or financial modeling.
Culture & Benefits
- Collaborative, innovative, diverse, and inclusive workplace.
- Focus on ethical business practices, equity, and belonging.
- Reasonable accommodations are available during the hiring process.
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