Data / ML Automation Intern

About this role

<div class="content-intro"><p><a href="https://www.xendit.co/en/">Xendit</a> provides payment infrastructure across Southeast Asia and is expanding to Greater China and LATAM. We process payments, power marketplaces, disburse payroll and loans, provide KYC solutions, prevent fraud, and help businesses grow exponentially. We serve our customers by providing a suite of world-class APIs, eCommerce platform integrations, and easy to use applications for individual entrepreneurs, SMEs, and enterprises alike.</p> <p>Our main focus is building the most advanced payment rails for Southeast Asia, with a clear goal in mind — to make payments across and within SEA simple, secure and easy for everyone. We serve thousands of businesses ranging from SMEs to multinational enterprises, and process millions of transactions monthly. We’ve been growing rapidly since our inception in 2015, onboarding hundreds of new customers every month, and <a href="https://techcrunch.com/2021/03/02/indonesia-payments-infra-startup-xendit-raises-64-6m/">backed by global top-10 VCs</a>. We’re proud to be featured on among the fastest growing companies by <a href="https://www.ycombinator.com/topcompanies">Y-Combinator</a>.</p></div><h3></h3> <h3>About the Job</h3> <p></p> <p><strong>Duration:</strong>&nbsp;6 months<br><strong>Type:</strong>&nbsp;Internship</p> <p>We’re looking for a Data / ML Automation Intern to help build reliable data workflows, reporting tools, and AI-assisted automations for operational teams. You’ll work across data engineering, analytics, machine learning, and software development to turn manual processes into scalable systems.</p> <h3>Minimum Qualifications</h3> <p></p> <ul> <li>Currently pursuing or recently completed a degree in Computer Science, Data Science, Statistics, Engineering, Information Systems, or a related field.</li> <li>Proficiency in Python and/or TypeScript.</li> <li>Basic SQL skills, including joins, aggregations, and filtering.</li> <li>Familiarity with data structures, APIs, Git, and software-development fundamentals.</li> <li>Interest in data engineering, machine learning, analytics, or automation.</li> <li>Comfortable working with imperfect data and learning unfamiliar systems.</li> <li>Able to communicate clearly in English and collaborate with technical and non-technical stakeholders.</li> </ul> <p></p> <h3>Preferred Qualifications</h3> <p></p> <ul> <li>Experience with GCP and BigQuery.</li> <li>Familiarity with dbt, Airflow, Databricks, Apache Kafka, or ETL/ELT pipelines.</li> <li>Exposure to machine learning libraries such as pandas, scikit-learn, PyTorch, or TensorFlow.</li> <li>Experience using LLM APIs, prompt engineering, agent workflows, or evaluation pipelines.</li> <li>Familiarity with Docker, Kubernetes, CI/CD, AWS, Terraform, or ArgoCD.</li> <li>Experience building dashboards with Looker Studio, Metabase, Tableau, Power BI, or similar tools.</li> <li>Personal projects involving data pipelines, automation, analytics, or machine learning.</li> </ul> <h3>Tech you may work with</h3> <p>Python, TypeScript, SQL, GCP, BigQuery, Databricks, dbt, Airflow, Kafka, Docker, Kubernetes, AWS, Terraform, ArgoCD, Git-based CI/CD, REST APIs, and LLM/ML tooling.</p> <p></p> <p></p> <h3>Responsibilities</h3> <p></p> <ul> <li>Build and maintain data pipelines for extracting, transforming, validating, and loading data.</li> <li>Write SQL queries for analysis, reporting, and data-quality checks.</li> <li>Develop automation scripts and internal tools using Python and/or TypeScript.</li> <li>Work with Google Cloud Platform (GCP), especially BigQuery, to manage and query datasets.</li> <li>Assist with workflow orchestration using tools such as Airflow or similar schedulers.</li> <li>Help develop, test, and monitor ML or LLM-powered automation workflows.</li> <li>Integrate internal systems and third-party APIs into data and automation pipelines.</li> <li>Support dashboarding, operational reporting, and data-quality monitoring.</li> <li>Document data models, pipeline behavior, and technical decisions.</li> <li>Participate in code reviews, debugging, and improving reliability of existing workflows.</li> </ul>