Job
Description
About Aplazo Aplazo is a fast-growing BNPL fintech startup redefining financial access for Mexicos underbanked population. Unlike traditional models, Aplazo serves as a cash alternative , enabling users to split payments online and in-store without a credit card empowering millions with greater financial freedom. With 40% of users lacking credit history , our AI-powered platform reduces credit risk and enables responsible lending. Over 50% of transactions occur in physical stores , proving our deep offline reach in a market where e-commerce remains limited. Backed by $110M in funding (including a recent $70M Series B ), Aplazo is rapidly scaling, helping merchants increase basket size, conversions, and customer loyalty through a tech-first approach . We're building Latin Americas most beloved fintech—one inclusive transaction at a time. Aplazo Story in Techcrunch : https://techcrunch.com/2024/05/13/aplazo/ About ML & AI Labs At Aplazo, our ML & AI team is central to driving innovation and business impact . We tackle high-stakes challenges across domains like risk, payments, personalization, growth, underwriting, fraud detection, and customer experience . Our team has built state-of-the-art credit risk and fraud models , leveraging alternative data and deep learning to serve Mexico’s underbanked population. With robust MLOps infrastructure —including automated CI/CD, model versioning, and real-time monitoring—we ensure scalable, reliable, and high-performing AI solutions. We’ve developed advanced recommendation systems, activation models, and dynamic pricing engines that significantly improve user engagement, marketing efficiency, and CAC optimization . Our work supports key business functions across the customer lifecycle. Highlights & Impact Lowest fraud rate in LATAM , powered by real-time ML inferencing Alternative data lending to drive inclusion for users with no credit history Reinforcement learning for personalized credit limit management Dynamic risk-based pricing to boost customer conversions End-to-end recommendation engine to tailor every user touchpoint Key Responsibilities Work closely with Growth, B2C product, Marketing, Sales, and Engineering teams to identify and prioritize data science projects. Translate complex data insights into actionable for non-technical stakeholders. Create and maintain a roadmap for data science projects that support growth objectives and ensure alignment with company goals. Define the vision for data science initiatives related to customer science, marketing science, and conversational AI for better customer acquisition, engagement, satisfaction, and retention. Promote an AI-first culture within the organization by advocating for the use of data in decision-making processes. Evaluate and integrate cutting-edge technologies and methodologies to keep Aplazo at the forefront of innovation. Understand the end-to-end ML pipeline (data gathering to production). Conduct Data Analyses; your analyses will decide which policies we adopt, where we expand our business, and with whom we partner. Represent Aplazo in industry conferences, webinars, and other public forums. Required Qualifications: Experience: Experience in AI-customer, especially in B2C (Business-to-Consumer), marketing, customer support, and customer growth relevant experience. Experience in developing cutting-edge customer science models for comprehensive customer personalisation, segmentation, rewards and referral systems, conversational AI, and recommendation engines. Experience designing and implementing strategies to enhance customer personalisation to improve customer engagement and retention. a proven track record of developing personalised customer experiences through data analytics and predictive modeling. Experience in growth hacking strategies to drive user acquisition and engagement using AI. Experience with CDPs and leveraging them to unify customer data from various sources for better insights and personalised experiences. Successful implementation of A/B testing, user segmentation, and personalisation to optimise marketing campaigns and marketing effectiveness. Experience working in highly dynamic work environments with a steep learning curve. Experience in statistical modeling, machine learning, data mining, unstructured data analytics, and natural language processing. Sound understanding of - Bayesian Modeling, Classification Models, Cluster Analysis, Neural Networks, Nonparametric Methods, Multivariate Statistics, etc. Leveraging innovation in applying AI to improve customer experiences, including experimenting with emerging technologies and methodologies. Years of experience: 6-12 years of experience in the technology sector, with a significant portion spent working directly with AI/ML technologies. Experience in leading and managing AI/ML projects and teams. Experience working with clients or customers in a leadership capacity, ideally in AI-focused roles. Technical skills: Python programming skill is a must. Strong coding capabilities in ML and Deep learning. Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI/ML services (e.g., SageMaker, Azure ML, Google AI Platform). Proficiency in project management tools (e.g., Jira, Trello) and agile methodologies (e.g., Scrum, Kanban) to manage AI projects effectively. Familiarity with database queries and data analysis processes. Expertise in NLP techniques and familiarity with tools and libraries like BERT, GPT, spaCy, and NLTK. Experience with various ML/DL algorithms and techniques. Ability to stay updated with the latest research in GenAI and deep learning. Soft skills: Proven leadership experience, including team building, mentoring, and managing cross-functional teams. Strong project management skills with experience in Agile and Scrum methodologies. Excellent verbal and written communication skills. Ability to explain complex technical concepts to non-technical stakeholders and customers. Strategic Thinking: Ability to align AI strategies with business goals and customer needs. Detail-oriented, with the ability to work both independently and collaboratively.
