About KueskiAt Kueski, we're dedicated to improving the financial lives of people in Mexico.
Since ****, 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 ****, 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 **** and ranked among the Best Companies for Female Talent by EFY.PositionKueski is seeking a Senior Data Scientist to develop and improve machine learning solutions that directly shape our products and customer experiences, with a strong focus on fraud detection and prevention.
This role is idóneo for an analytical and pragmatic Data Scientist with strong quantitative foundations who is passionate about applying machine learning to product development and solving meaningful business problems, particularly those related to identifying, modeling, and mitigating fraudulent behavior across our lending and payments products.
You will combine machine learning, deep-dive analytics, experimentation, and strong business understanding to develop and improve our products.
You will own machine learning models throughout their lifecycle, from experimentation and feature engineering to production monitoring and continuous improvement, while contributing to structured and reliable ML pipelines using modern open-source technologies and cloud-based tools.




Reporting to the Manager of Data Science, you will work autonomously with cross-functional teams, provide technical input throughout the product development lifecycle, and help raise the technical capabilities and performance of the broader team.Key ResponsibilitiesBuild and improve Kueski's products through machine learning and data analytics, partnering with Product, Engineering, Risk, and Business teamsOwn production ML models end-to-end, monitoring performance, analyzing user and model behavior, and addressing anomalies or underperformanceLeverage AI-enabled tools and emerging AI capabilities to accelerate analysis, experimentation, and model development, while identifying opportunities to improve products and business outcomesDevelop model experiments and features, and contribute to reliable, well-documented production ML pipelinesProvide Data Science expertise throughout the product development lifecycle, including defining requirements for engineering work that impacts ML solutionsWork autonomously across teams to design and deliver high-impact product enhancementsMentor team members, promote technical excellence through pairing and code reviews, and support technical recruiting when neededCollaborate with Machine Learning and Software Engineers to strengthen testing and quality processes for production modelsExperienceQuantitative background such as Engineering, Physics, Mathematics, or equivalent practical experienceHands‐on experience using AI‐powered tools and emerging AI technologies to improve Data Science workflows, experimentation, analysis, or product solutionsStrong analytical and communication skills,



with the ability to explain complex topics to technical and non-technical audiencesAdvanced understanding of machine learning and hands‐on experience applying ML in academic or industry settingsProven ability to solve business problems with cross‐functional teams and influence stakeholders constructivelyDemonstrated autonomy delivering high‐impact Data Science projects, contributing to team performance, and mentoring junior team membersStrong Python and ML libraries experience, solid SQL proficiency, and comfort working in Unix‐like environmentsAbility to quickly learn and adopt new technologies and methodologiesFluency in English and the ability to communicate clearly with non-technical audiencesNice to haveExperience detecting organized or coordinated fraud using graph analytics, network science, or device fingerprinting/behavioral biometrics.Experience designing or improving hybrid rule‐based + ML systems for real‐time decisioning (e.G. transaction authorization, origination scoring).
Familiarity with relevant fintech regulatory frameworks (AML, KYC) and their intersection with fraud detection models.Background in Risk, Economics, or Pricing, with the ability to apply this knowledge to credit or customer behavior decisions.Experience with AWS machine learning servicesExperience applying causal inference techniques, such as uplift modeling or treatment effect estimation, particularly in offering and optimization use cases.Background in Economics, Econometrics, Finance, or financial modeling, with the ability to apply this knowledge to credit, pricing, and customer behavior decisionsDiversity & InclusionAt 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.
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📌 Senior Data Scientist (Jalisco)
🏢 Kueski
📍 Jalisco