Job Title: Applied Scientist ML/AI Intern Location: Remote (Based in Bangalore) Company: Aplazo – Latin America’s Leading BNPL Fintech About Aplazo Aplazo is a fast-growing BNPL fintech transforming financial access in Latin America. Backed by $110M in funding , we empower users to split payments without credit cards , promoting financial inclusion . Our cutting-edge ML and AI infrastructure drives impactful solutions across risk, fraud, recommendations, and growth . Role Overview As a Data Science Intern (ML/AI) , you’ll work on high-impact, real-world projects in areas like credit scoring, fraud detection, personalization, and recommendations. You'll gain end-to-end experience in model development, deployment, and evaluation. Key Responsibilities Assist in building ML models for credit risk, fraud detection , and personalization Analyze alternative data (e.g., bank statements, mobile data) Contribute to model deployment pipelines and monitoring Perform EDA, data cleaning , and support business initiatives Collaborate with cross-functional teams on data-driven solutions Required Skills Strong Python skills for ML and data analysis Familiarity with deep learning (CNN, RNN, transformers, NLP) Good understanding of ML/GenAI algorithms and best practices Excellent problem-solving , communication , and collaboration skills Preferred Background Bachelor's or Master’s in CS, Stats, or related fields Exposure to AWS/Google Cloud , GenAI models , or Spanish is a plus Publications or conference presentations in ML/DS (nice to have) Why Join Us? Work with a world-class data science team Build solutions for millions of users across Latin America Gain hands-on exposure to cutting-edge MLOps and GenAI Potential for Pre-Placement Offer (PPO) for outstanding performance If you're ambitious, curious, and ready to make an impact , we’d love to hear from you!

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.

About Aplazo Aplazo is a Mexican BNPL startup redefining financial access for the underbanked. Unlike its global counterparts, Aplazo isnt just about debtits an alternative to cash, offering fair, simple, and transparent financial solutions. Founded four years ago, Aplazo enables users to split payments online and in-store without a credit card, empowering financial freedom and opportunity across Latin America. Our tech-driven approach minimizes credit loss while ensuring accessibility—even for the 40% of users with no credit history. With in-store transactions making up more than half of our business, we bridge the gap in Mexico’s evolving financial landscape. Merchants benefit from increased basket sizes, higher conversions, and stronger customer engagement. Backed by $110M in funding , Aplazo is poised for continued innovation. We’re building Latin America’s most beloved fintech and are seeking passionate technologists and leaders who thrive on collaboration, quality, and impact . Aplazo on TechCrunch : https://techcrunch.com/2024/05/13/aplazo/ About Data Science @ Aplazo The Data Science team at Aplazo is a strategic driver of innovation and transformation. With a strong product-first mindset and deep technical expertise, we solve complex problems across risk, payments, personalization, fraud detection, marketing, customer lifecycle, recommendations, underwriting, and more. A cornerstone of our success is our robust MLOps infrastructure —featuring automated CI/CD pipelines, model and data versioning, and comprehensive observability to support a seamless end-to-end ML lifecycle. Now, we are investing in next-generation MLOps capabilities to further scale and future-proof our systems. Role Overview We are seeking a visionary Lead/Staff MLOps Engineer to lead the evolution of our ML infrastructure. This is a high-impact role for a technical leader who thrives on building scalable platforms, accelerating experimentation workflows, and enabling high-velocity AI development. You’ll define the MLOps roadmap, establish best practices, and build resilient systems that empower our Data Science and Engineering teams to operate at scale. You will work closely with stakeholders across Product, Growth, Engineering, and Data to translate complex business goals into reliable, high-performing machine learning systems. Key Responsibilities Architect scalable ML systems with a focus on reliability, security, automation, and performance Lead the end-to-end MLOps strategy : CI/CD for ML, model registries, feature stores, testing, deployment, and monitoring Drive innovation across ML domains (LLMs, NLP, personalization, fraud detection, pricing, customer science) Optimize ML workflows for cost, latency, reproducibility , and resource efficiency Define rigorous model governance standards including auditability, reproducibility, versioning, rollback mechanisms Evaluate and integrate new technologies (LLMOps, Foundation Models, LangChain, etc.) through structured POCs Serve as technical mentor and thought leader , influencing teams and instilling engineering excellence Partner with executive leadership on quarterly OKRs aligned to risk-adjusted growth, profitability, and model performance Collaborate across geographies—Mexico, USA, Chile, and Europe—to ensure strategic alignment Required Qualifications Experience 6+ years in MLOps, ML Engineering, or Software Engineering, with 2+ years in a senior leadership role Proven success in building and scaling production-grade ML platforms Strong exposure to cloud-native infrastructure (GCP or AWS preferred) Experience deploying AI/GenAI systems in regulated environments Technical Skills Expert in Python and ML stack (TensorFlow, PyTorch, Scikit-learn, LangChain, OpenAI APIs) CI/CD tools (GitHub Actions, Argo, Kubeflow, MLflow) Kubernetes, Docker, ONNX, TorchServe for model serving and orchestration Strong with data warehousing and processing tools (BigQuery, Snowflake, Spark, Kafka, Flink) Experience with metadata management , feature stores , model versioning , A/B testing , and monitoring systems Familiarity with LLMOps, DataOps (Airflow, dbt), and streaming architectures Soft Skills Exceptional leadership and mentoring skills Excellent written and verbal communication Ability to work independently and cross-functionally in a fast-paced environment Preferred Qualifications Bachelor’s or Master’s in Computer Science, Statistics, or related field (Tier-I institutions preferred) PhD in Data Science, Machine Learning, or related field (with 8+ years of relevant experience) Publications or conference presentations in ML/AI/DS fields Spanish language proficiency is a plus Nice to Have Experience in fintech, risk, fraud, or payments Exposure to model fairness, explainability, and responsible AI frameworks Familiarity with LLMOps stacks (OpenLLM, LangChain, Guardrails) and prompt engineering for GPT-based models Languages English: Advanced proficiency Spanish: Nice to have Why Join Us Competitive salary and equity Remote-first flexibility + in-person offsites Annual learning budget + global conference participation Ownership-driven culture, fast iteration cycles, low bureaucracy

Responsibilities As a Data Science (ML and AI) Intern, you won't be working on side projects; you'll be tackling real problems, influencing product direction, and working alongside a team that believes in asking why, not just how. Assist in developing and improving credit and fraud risk models using machine learning, deep learning, and rules-based approaches under the guidance of senior data scientists. Support the analysis of alternative data sources (e. g., mobile device data, bank statements) to enhance risk assessment and decision-making models. Help build and evaluate models related to customer behavior, including personalization, recommendations, referrals, and transaction categorization. Learn and contribute to the end-to-end machine learning pipeline from data collection and preprocessing to model development and basic production deployment. Participate in monitoring and evaluating the performance of models in production, learning how to identify issues and suggest improvements. Assist in data gathering, cleaning, and exploratory data analysis to support various data science projects and business initiatives. Engage with business and technical stakeholders to understand their data needs and help identify potential data-driven solutions. Notable Achievements Achieved the lowest fraud rate in LATEM markets by leveraging the very high capabilities of our multiple fraud detection models with real-time inferencing. Alternative data lending - built capabilities to extend credits to the underbanked segment in Mexico markets, fostering financial inclusion and financial freedom for everyone. Advanced reinforcement learning models and deep learning models to achieve hyper-personalisation for credit limit changes. Incorporated the Dynamic Risk-Based Pricing model to optimize the customer conversion rate. Developed a recommendation engine to personalize all communication to the end user. Requirements Proficient in Python programming, with a focus on coding for machine learning and deep learning applications. Strong in data analysis and data wrangling. Follow industry best practices and stay up to date with the latest machine learning/ GenAI algorithms and techniques to drive innovation. Knowledge of deep learning concepts like CNN, RNN, tokenization, transformers, and various NLP techniques. Bachelor's or Master's degree in Computer Science, Information Management, Statistics, or related field. Soft Skills Highly curious and passionate about problem-solving, with a strong drive to uncover insights and optimize solutions. Exceptionally detail-oriented, capable of working both independently and collaboratively in a fast-paced environment. Excellent communication skills, with the ability to translate complex concepts into clear, actionable insights for both technical and non-technical stakeholders. Energetic and proactive, with a strong learning aptitude and the audacity to take on challenges beyond their comfort zone. Not afraid to go above and beyond, demonstrating initiative and ownership in tackling tough problems. Nice To Have Publications or presentations in recognized Machine Learning and Data Science journals/conferences. Experience with cloud services (like AWS or Google Cloud) and understanding of distributed systems. Exposure to GenAI models. Languages: Spanish, English (Level: advanced). This job was posted by Ankur Pal from Aplazo.