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Our mission is to transform international supply chains to be more resilient by helping logistics companies realize the full potential of their data. We cater to both shipping lines and cargo airlines, covering 90% of the world trade volume that travels via ocean and 35% of the world trade value that travels via air. We use proprietary machine learning algorithms and real-time external market data (such as economic indices, marine weather, satellite-based data, etc.) to predict how much cargo will be shipped, when it will arrive, and deliver actionable insights.

We are excited to be a fast-growing team of software engineers, data scientists, and industry experts. Based out of Singapore, we’ve been building together since 2018, and are backed by some of the leading investors, including Wavemaker Partners, Entrepreneur First, SGInnovate, and Investigate VC.

We are customer-obsessed and are constantly working to provide our customers access to actionable and insightful data to build resilient supply chains.

About the Role:

You will be joining the Tech Team as an Analytics Manager, where you will work with a small team of Data Analysts and report directly to the VP of Technology. In this critical role, you will be responsible for KPI management, quality assurance, and analytics dashboards.

You will work on a data-heavy product that offers our customers end-to-end visibility of their cargo at each step of the ocean movement. Our prediction engine answers when, where, why, and by how many days the container would be delayed. You will ensure that the data ingested in the model and shared with the customers is error-free and of the highest quality. You will own internal performance dashboards and automation processes while contributing directly to data analysis and visualization.

What You Will Do Data KPIs Management: Maintain all data KPIs and address customer-specific questions and issues. Serve as the point of contact between Customer Success and Data Analytics. Analytics Dashboard Ownership: Own and manage internal and customer analytics dashboards, addressing issues reported by customers, preparing reports for customer calls, and defining requirements for data insights. You will work closely with customer and product team to help create customer specific and overall reports on regular basis. Hands-On Technical Work: Remain actively involved in technical tasks using Python and SQL for data analysis, report generation, and data visualization. This role is 60% hands-on technical work and 40% people management. Collaboration: Support engineering and data science teams in system-level data fixes. Understand how the engine makes predictions and explore possible improvements by fixing or introducing new data/features. Cross-Department Support: Support the customer success, sales, and marketing teams in gaining insights from the data, such as performance, accuracy metrics, and the impact of real-time events for customer calls or marketing efforts. Problem Solving: Identify and resolve anomalies, perform root cause analysis of prediction issues, and propose solutions for QA process improvements. Team Leadership: Lead and mentor a team of Data Analysts, fostering a collaborative and proactive work environment. To thrive in this role, you must have Bachelor's or Master's Degree in CS, Data, Engineering or a related field. Minimum 5 years of experience in analytics, with a current role as a Senior Analyst or Analytics Manager. Prior experience leading a small team. Excellent proficiency in Python and SQL, with the ability to write reusable, scalable code. First Principles thinking/approach: Excellent problem-solving skills with a proactive initiative to address challenges. Collaboration: Ability to collaborate effectively with stakeholders across various departments. Excellent communication skills Experience in a product-based company, preferably within a startup environment with early-stage technical product development. Strong academic background in a technical field, with a proven track record of advancing in a technical career. Proven experience with data visualization tools and techniques. Detail-Oriented: An eye for detail and the ability to identify anomalies in the system. Empathy and Urgency: Ability to empathize with customer pain points and respond promptly on a day-to-day basis. Communication: Fluent in written and verbal English, with the ability to clearly convey complex technical concepts. Good to Have: Basic understanding of machine learning algorithms. If you are a strategic problem solver, data-driven Analytics Manager with a passion for growth and innovation, and are ready to take a hands-on approach in a fast-paced startup environment, we would love to hear from you.