Supply Chain / Predictive Analytics · India
Portcast builds predictive supply chain analytics, helping shippers, manufacturers and logistics service providers turn data into decisions and decisions into action. Its models forecast container arrival times, port congestion and demand patterns using a combination of carrier data, vessel tracking, weather and historical performance — a genuinely hard prediction problem, because the ground truth is a physical global system with weather, labour and geopolitical shocks in it. The value to customers is concrete: knowing a shipment will be five days late while there is still time to react is worth considerably more than knowing it afterwards. The company works with an industry at what it describes as a critical inflection point, as logistics moves from spreadsheets and phone calls to data-driven planning. Portcast is headquartered in Singapore and operates with a small, technically dense team, which means analysts and engineers see the whole pipeline from raw data to customer-facing prediction rather than one slice of it. For an early-career data analyst, the appeal is working on forecasting problems where the data is messy, the domain is real and the output is used operationally.
2–3 DSA coding problems on HackerRank, CodeSignal, or company platform
Data structures & algorithms — arrays, trees, graphs, dynamic programming
System design or low-level design — scalability, APIs, databases
Career goals, teamwork, strengths/weaknesses, role expectations