Portcast - Data Analyst Intern
Requirements
• Currently pursuing (Final-year student) or recently completed a degree in Computer Science, Data Analytics, Data Science, Engineering, Information Technology, Statistics, or a related field. • Working knowledge of Python and SQL, you don't need years of experience, but you should be able to write a query and a script and want to get sharper fast. • Prior internship experience in a Data Analyst or Business Analyst role, preferably in a product-based, lean startup particularly in logistics, ecommerce or B2B SaaS data-heavy domain. • Willing to learn over "already knows everything": we hire interns for curiosity and effort. You put in the work to understand our domain, product, data, and customers. • Curious by Default: when the data surprises you, you chase the why. You ask good questions early and treat every gap as something worth understanding. • You own your output, AI included. You can use AI tools to move faster, but you read and validate what they produce, you don't just paste it. If one day the tool isn't there, you can still write the query yourself. You can explain what you did and why, without saying "the AI did it." • An eye for detail: you notice when a number looks wrong before anyone else does. • Empathy and urgency: you understand that clean data is what customers are counting on, and you move promptly day to day. • Fluent in written and verbal English, and comfortable working in a diverse, fully remote team.
Benefits
• Real work from day one: you'll touch live data and integrations that customers actually depend on. • Mentorship: you'll learn directly from our Data Analysts and Data Scientists. • A path to permanent: strong & exceptional A+ player interns here have a real shot at converting to a full-time role. • Globally distributed, lean team remote-first flexibility: work with a fully distributed team across Asia and Europe, built on trust, accountability, and collaboration. • Our CORE Values Guide Everything We Do: • Curiosity: We read the data before we trust it. We dig into why a number looks the way it does, not just how to make the anomaly disappear. • Ownership: We act like owners, not ticket-takers. We stay on a problem until it's actually fixed at the source. • Raising the bar: We don't settle for a report that only works this once. We aim for data pipelines and dashboards that are reliable, reusable, and easy for the team to trust. • Effectiveness: We focus on analysis that creates real product and customer impact. We prioritize the right problems, make practical trade-offs, and ship work that improves outcomes, not just output. • We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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