Senior Data Scientist

At Kueski, we're dedicated to improving the financial lives of people in Mexico. Since 2012, we've been the leading buy now, pay later (BNPL) and online consumer credit platform in Latin America, known for our innovative financial services. Our flagship product, Kueski Pay, provides seamless payment solutions for both online and in-store transactions, establishing itself as the preferred option for nearly 30% of Mexico's top e-commerce merchants. Notably, we were the first to introduce BNPL on Amazon Mexico.

We're a tech company with a culture geared toward innovation, collaboration, and impact, fostering a strong, diverse, and inclusive workplace. Our commitment to excellence and ethical business practices has earned us multiple industry recognitions. In 2024, we were named one of the World’s Top FinTech Companies by CNBC and recognized as one of the most ethical companies in Mexico by AMITAI. Additionally, we were certified as a Best Place to Work for LGBTQ+ Equality by HRC Equidad MX 2025 and ranked among the Best Companies for Female Talent by EFY.

Kueski is seeking a Senior Data Scientist to build, deploy, and continually improve machine learning solutions that expand access to financial products for the many Mexicans underserved by traditional banking. This role is ideal for an analytical IC with strong quantitative foundations, practical problem-solving instincts, and a passion for applying ML to real products at scale.

As a key contributor, you’ll partner closely with ML Engineering, Software Engineering, Risk, Analytics, and Product to own production models, dig deep into data, and ship reliable, business-impacting ML pipelines using state-of-the-art open-source libraries and cloud technologies.

• Build, shape, and improve products through ML and data analytics with partners in Product, Engineering, Risk, and Business.

• Perform deep-dive analyses on product performance, user behavior, model usage, and underperforming segments.

• Work autonomously with cross-functional teams to design and deliver product enhancements

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• Own production ML models: monitor KPIs, ensure performance stays within thresholds, and take corrective action on deviations.

• Develop new experiments and features; contribute to reliable, structured ML pipelines.

• Collaborate with MLEs and QA engineers to define testing and QA processes for production models.

• Participate in the product development lifecycle; provide technical input and define requirements for engineering work that affects data science.

• Produce clear documentation for production pipelines (features, algorithms, hyperparameters, KPIs, business context).

• Conduct ad-hoc analyses to investigate anomalies or degradations.

• Mentor teammates, promote technical excellence, and provide code reviews and constructive feedback.

• Support recruiting processes (challenge evaluation, interviews) as needed.

• Quantitative background (e.g., Engineering, Physics, Mathematics) or equivalent experience.

• Advanced understanding of ML algorithms with hands-on application in academia or industry.

• Proven experience partnering cross-functionally to solve business problems with ML.

• Demonstrated autonomy delivering high-impact data science projects; track record of measurable outcomes.

• Ability to mentor junior team members; collaborative through pairing and code reviews.

• Strong analytical skills; excellent written and verbal communication for technical and non-technical audiences.

• Strong Python (pandas, NumPy, matplotlib) and common ML libraries; solid SQL; comfortable in Unix-like environments.

• Ability to quickly learn and adopt new technologies and methodologies.

• Languages: English fluency (required).

At Kueski we embrace diversity in all forms, systematically promote equity, and ensure everyone feels included with a sense of belonging. We are committed to the full inclusion of all qualified candidates. As part of this commitment, we will make efforts to ensure reasonable accommodations are made during the hiring process. If reasonable accommodation is needed, please let the Talent Acquisition team know.