Data Science intern

DEUNASan Francisco, CA

About The Position

DEUNA is a rapidly growing startup revolutionizing global commerce with ATHIA, our AI-powered orchestration and payments platform that helps large enterprises boost approval rates, reduce costs, and unlock new revenue. Built by the team behind DEUNA—the fastest-growing Commerce OS in Latin America—ATHIA combines payment intelligence, checkout optimization, and data orchestration in one powerful solution. With deep integrations across 300+ PSPs and alternative payment methods, and over 20% of Mexico’s digital economy running through our platform, we simplify global payments through a single integration and centralized reconciliation. We are a rapidly growing startup expanding into the U.S. to meet the urgent needs of large retailers, marketplaces, airlines, and QSRs. Join us to shape the future of payments! Visit https://www.deuna.com/ to learn more about us! We are looking for curious, analytical, and motivated students who are eager to learn about Data Science in a fast-paced technology environment. During the internship, you will support the Data team by analyzing data, building models, developing insights, and contributing to projects that have a direct impact on our products and business. This is an educational, unpaid internship designed to provide practical experience, mentorship, and exposure to real-world data science projects.

Requirements

  • Currently pursuing a Bachelor’s or Master’s degree in: Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, Physics, Or a related quantitative field.

Responsibilities

  • Assist in collecting, cleaning, and preparing datasets for analysis.
  • Perform exploratory data analysis to identify trends and patterns.
  • Support the development and evaluation of machine learning models.
  • Build dashboards and visualizations to communicate business insights.
  • Collaborate with Data Scientists, Data Engineers, and Product teams on ongoing initiatives.
  • Document analyses, methodologies, and project findings.
  • Participate in team meetings, knowledge-sharing sessions, and technical discussions.
  • Learn and apply best practices in data science, experimentation, and analytics.
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