Scan your resume against ATS criteria for this Senior Data Scientist role at Kueski.
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 consumer credit platform in Latin America, known for our innovative financial services. Our flagship product, Kueski Pay, provides seamless payment solutions for both 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 of the World’s Top FinTech Companies by CNBC and recognized as 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
based in Guadalajara to develop and improve machine learning solutions that directly shape our products and customer experiences.
This role is ideal 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.
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.
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.
Build and improve Kueski’s products through machine learning and data analytics, partnering with Product, Engineering, Risk, and Business teams
Own production ML models end-to-end, monitoring performance, analyzing user and model behavior, and addressing anomalies or underperformance
Leverage AI-enabled tools and emerging AI capabilities to accelerate analysis, experimentation, and model development, while identifying opportunities to improve products and business outcomes
Develop model experiments and features, and contribute to reliable, well-documented production ML pipelines
Provide Data Science expertise throughout the product development lifecycle, including defining requirements for engineering work that impacts ML solutions
Work autonomously across teams to design and deliver high-impact product enhancements
Mentor team members, promote technical excellence through pairing and code reviews, and support technical recruiting when needed
Collaborate with Machine Learning and Software Engineers to strengthen testing and quality processes for production models
Quantitative background such as Engineering, Physics, Mathematics, or equivalent practical experience
Hands-on experience using AI-powered tools and emerging AI technologies to improve Data Science workflows, experimentation, analysis, or product solutions
Strong analytical and communication skills, with the ability to explain complex topics to technical and non-technical audiences
Advanced understanding of machine learning and hands-on experience applying ML in academic or industry settings
Proven ability to solve business problems with cross-functional teams and influence stakeholders constructively
Demonstrated autonomy delivering high-impact Data Science projects, contributing to team performance, and mentoring junior team members
Strong Python and ML libraries experience, solid SQL proficiency, and comfort working in Unix-like environments
Ability to quickly learn and adopt new technologies and methodologies
Fluency in English and the ability to communicate clearly with non-technical audiences
Based in Guadalajara, Mexico
Experience 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 services
Experience 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 decisions
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.
How to apply for Senior Data Scientist at Kueski?
Click the "Apply on Company Website" button on this page to submit your application directly on the employer's official portal.
What is the salary for this role?
Salary details will be discussed during the interview.
What experience is required?
This position is open to freshers and experienced candidates.
Is this position still open?
Yes, currently active and accepting applications.
Explore related active roles in data_science
Senior Data Scientist
Kueski · Guadalajara
