We are looking for an experienced Data Scientist to join our Risk Analytics team, working on critical decision-making systems.

You will work on end-to-end ML solutions that support key risk processes. The role is strongly focused on production-grade Machine Learning, with increasing emphasis on building scalable, reliable, and explainable models used in daily risk decisioning.
Challenges that await you:

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- Develop and improve ML models for credit application approval and credit limit assignment
- Build ML-based decision frameworks and analytical tools for credit portfolio management
- Translate business problems (risk, profitability, growth) into data science solutions
- Work end-to-end: data analysis, feature engineering, model training, validation, and deployment
- Collaborate with product, risk, and portfolio teams to ensure models drive measurable business impact
- Continuously improve existing models and pipelines in a production environment
- Balance model performance, interpretability, and business constraints

What makes you a great fit:

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- 4+ years of professional experience as a Data Scientist
- Strong, hands-on experience with Machine Learning in production
- Proven track record of delivering measurable business impact using ML
(e.g. revenue uplift, cost reduction, risk improvement, user growth)
- Experience deploying models end-to-end — from idea to production
- Solid understanding of classical ML and modern approaches
- Mathematical or technical education from the following universities: MSU, MIPT, HSE, MSTU, MEPhI, NSE (preferred)
- Ability to explain complex models and results to non-technical stakeholders
- Experience in fintech, credit risk, or portfolio management is a strong plus

Our ways of working:

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- Innovative Spirit: A commitment to creativity and groundbreaking solutions
- Honest Feedback: valuing open, transparent communication
- Supportive Team: a strong, collaborative community
- Celebrating Achievements: recognizing our wins toge

📌 Senior Data Scientist (Ciudad de México)
🏢 Plata Card
📍 Ciudad de México