Aplazo is Mexico's leading BNPL platform, built for a market where 40% of users have no credit history and traditional credit checks simply don't work. We operate at the intersection of financial inclusion and technology, enabling millions of Mexicans to make fractionated payments online and in-store without a credit card. We've cracked alternative data lending at scale, achieving the lowest default rates in LATAM while growing rapidly. With $110 million raised across Series A+ and Series B, we are well-capitalised and growing across every vertical.
Data Science at Aplazo is deeply embedded in how the business runs, not a separate function that hands off work downstream. The team works closely with Credit, Fraud, Collections, Growth and Product to build and own models that run in production and directly shape business decisions.
Most data science roles ask you to go deep in one domain. This one asks you to go wide, and still be excellent.
As a Senior Data Scientist, you'll work across Credit Risk, Growth, and AI initiatives based on where the team needs the most leverage at any given time. Some quarters that means contributing to a fraud model. Others it means owning a personalization or growth experiment end-to-end. You'll be expected to ramp quickly, work with high autonomy, and deliver without needing a fully paved path.
This role is critical to how we scale, it creates the flexibility and redundancy the team needs to execute across a wide roadmap without breaking.
Contribute across Credit Risk (underwriting, fraud, collections), Growth (personalization, recommendations, incentivization), and AI initiatives based on team priorities
Own projects end-to-end within your assigned domain, data, modeling, deployment, and post-launch monitoring
Develop deep familiarity across multiple domains and systems, enabling the team to move faster and maintain continuity as we scale
Drive research and exploration workstreams, evaluating new modeling approaches, alternative data sources, and tooling that keeps Aplazo ahead of the curve
Collaborate closely with Lead and Staff Data Scientists to deliver on the broader roadmap
Identify and flag opportunities for improvement across domains, you'll often be the person with the broadest view of what's working and what isn't
Must-haves
4–8 years of experience across more than one data science domain, Risk, Growth, Personalization, or similar
Strong ML fundamentals, you can pick the right tool for the problem rather than defaulting to what you know best
Demonstrated ability to ramp quickly on unfamiliar problems and deliver with limited guidance
Proficiency in Python, SQL, and standard ML frameworks
Hands-on experience with LLMs / GenAI as part of your regular workflow
Production experience, you've taken models past the notebook stage
Strong Plus
Fintech or BNPL background, familiarity with credit risk or fraud modeling concepts
Experience with experimentation frameworks and A/B testing at scale
Exposure to MLOps practices, feature pipelines, model monitoring, deployment
Publications or presentations in recognized Machine Learning and Data Science journals / conferences
Aplazo operates as an AI-first company, AI is embedded in how we build, not bolted on. We're looking for someone who has genuinely changed how they work because of AI, using it to move faster, explore more, and reduce time spent on low-value tasks. Breadth is a strength in this role, and AI tooling is a big part of how you maintain quality across multiple domains.
The best person for this role is someone who brings genuine curiosity across domains and takes ownership without needing a fully defined problem. You'll work with a high degree of autonomy, and the breadth of your contribution will matter as much as the depth.
Rare opportunity to build breadth across Risk, Growth, and AI at a company where all three domains actually matter
Small, senior team, you'll work alongside and learn from some of the strongest DS practitioners in fintech
Direct impact on business outcomes, no layers, no hand-offs
Strong foundation for a future specialist or lead role as the team scales
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