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Portcast is a venture-backed Singapore-based logistics technology startup building a real-time transportation visibility platform for global supply chains. The company helps shippers, manufacturers, and logistics service providers turn data into actionable decisions, enabling them to prevent detention and demurrage, accelerate exception management, and close invoices faster.
As a Data Analyst reporting to the Analytics Manager, you will own data quality and integrity for a data-heavy product that provides end-to-end cargo visibility across ocean journeys. Your core responsibilities include:
• Documentation, reporting, and root-cause analysis of prediction issues, owning problems end-to-end rather than just flagging them
• Analyzing ingested and system-generated data for anomalies and gaps, tracing issues to their source and fixing processes to prevent recurrence
• Automating performance and accuracy review processes, report generation, and data visualization using Python and SQL to build reusable, scalable workflows
• Supporting Engineering and Data Science teams on system-level data fixes and exploring prediction improvements
• Maintaining and owning internal and customer dashboards tracking prediction accuracy, timeliness, coverage, and explainability
• Collaborating with Customer Operations and Marketing to surface data-driven insights and performance metrics
You will work closely with Data Science, Engineering, Product, and Commercial teams in a distributed, remote-first environment spanning Asia and Europe.
Required qualifications: Bachelor's or Master's degree in Computer Science, Engineering, IT, or related field; 2-3+ years as a Data Analyst or Business Analyst in product-based startups, ideally in logistics, e-commerce, or B2B SaaS; exceptional proficiency in Python and SQL with demonstrated ability to produce reusable, scalable code; strong attention to detail and ability to surface anomalies proactively; first-principles thinking with clear articulation of constraints and trade-offs; curiosity-driven approach to root-cause analysis; experience working in diverse, cross-cultural teams with strong ownership mindset.
Desirable: basic understanding of machine learning algorithms; experience with AI tools (Claude, Copilot) for QA and automation with clear validation practices.
