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Senior Data Scientist

Kueski, Inc.

Job Overview

Location

Remote

Job Type

Full-time

Full Job Description

📋 Description

• Own the end-to-end lifecycle of high-impact machine-learning models that decide whether millions of Mexicans get fair, fast access to credit. From exploratory data analysis to A/B testing in production, you will be the technical lead who turns raw data into measurable financial inclusion.
• Design, train, and deploy credit-risk, fraud-detection, and recommendation models that run 24/7 on AWS, process terabytes of behavioral and transactional data, and return sub-second predictions at 99.9 % uptime. You will choose algorithms, craft features, tune hyper-parameters, and write production-grade Python that scales horizontally with Spark and Kubernetes.
• Partner daily with ML Engineers, Backend Engineers, Risk Analysts, Product Managers, and Designers to translate business questions into rigorous data experiments. You will sit in sprint plannings, shape OKRs, and translate model outputs into clear product actions that increase approval rates while keeping loss rates within board-level targets.
• Establish and monitor real-time dashboards that track model drift, data quality, and business KPIs. When a metric slips, you will lead root-cause analyses, ship hot-fixes, and communicate impact to executives in plain language backed by statistical evidence.
• Deep-dive into customer behavior to uncover hidden segments and new opportunities. Examples: identify gig-economy workers who repay faster than predicted, quantify the impact of seasonal cash-flow spikes, or discover that a new data source (e.g., telco top-ups) improves Gini by 3 points.
• Champion reproducible science and engineering excellence. You will write unit-tested modules, enforce code-review standards, and maintain a living knowledge base so that every experiment is traceable and every model is reproducible six months later.
• Mentor junior data scientists through pair programming, design reviews, and career coaching. You will run weekly learning sessions on topics like uplift modeling, causal inference, or MLOps best practices, raising the bar for the entire 30-person data organization.
• Influence the technical roadmap by evaluating new open-source libraries, cloud services, and academic research. You will prototype with PyTorch, LightGBM, Vertex AI, or whatever tool gives Kueski the next 1 % edge, then socialize findings through internal tech talks and white-papers.
• Contribute to a culture of ethical AI. You will audit models for bias across gender, age, and geography; propose fairness constraints; and ensure that every algorithm we ship complies with Mexican fintech regulations and our own Responsible AI charter.
• Represent Kueski externally by speaking at meetups, publishing anonymized case studies, and collaborating with universities. Your work will be showcased as the gold standard for inclusive fintech AI in Latin America.

🎯 Requirements

• Quantitative degree (Engineering, Physics, Mathematics, Statistics, Computer Science) or equivalent experience
• 4+ years applying machine-learning models to real-world, large-scale problems in industry
• Expert-level Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) and SQL; comfort with Unix, Git, Docker, and cloud ML pipelines
• Demonstrated autonomy delivering end-to-end data science projects that drove measurable business outcomes
• Strong written and verbal communication in English; able to explain complex models to non-technical stakeholders

🏖️ Benefits

• 100 % remote-first culture with flexible hours and a monthly co-working stipend
• Competitive compensation package including equity and annual performance bonus
• Annual professional-development budget (courses, conferences, certifications) and paid learning time
• Comprehensive health insurance for you and your family plus mental-wellness and childcare allowances

Skills & Technologies

Python

Pandas

NumPy

Data Science

Senior

Remote

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Kueski, Inc.

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About Kueski, Inc.

Mexico-based fintech that underwrites and disburses unsecured consumer loans through its online platform, using alternative data and machine-learning models to assess credit risk for underbanked individuals. Founded in 2012, it provides instant micro-loans paid via SPEI, buy-now-pay-later checkout financing for e-commerce merchants, and employee salary-advance products. Operations span Mexico and select Latin American markets, partnering with retailers and payroll systems to embed lending at the point of sale.

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