An AI-driven logistics SaaS platform that optimizes complex supply chain networks is seeking a Solution Engineer to serve as the analytical backbone for their pre-sales and solutioning efforts.
The Ideal Profile :
- Experience: 7+ years of overall experience, with 36 years specifically in logistics modelling, supply chain analytics, BI, or simulation engineering. Prior exposure to the US market and handling US clients is mandatory.
- Technical Stack: Robust proficiency in Excel, SQL, and Python for data manipulation, coupled with expertise in BI tools like Power BI, Tableau, Qlik, or Looker.
- Domain Knowledge: Deep understanding of logistics operations, including FTL/LTL, last-mile delivery, routing, and multi-constraint network planning.
- Key Capabilities: Proven ability to build high-fidelity simulations, develop KPI packs, and present data-backed ROI models to CXO-level stakeholders and Operations Heads.
Key Responsibilities
- Develop and deploy advanced simulation models to evaluate supply chain performance, enabling stakeholders to make data-backed decisions under various market scenarios.
- Architect end-to-end analytics solutions by leveraging Python and SQL to extract, clean, and process large-scale logistics datasets for high-impact reporting.
- Lead presales engagements by demonstrating the value of our analytical tools to prospective clients, ensuring technical alignment with their specific operational challenges.
- Create intuitive dashboards and visual narratives using Power BI and Tableau to communicate complex optimization insights to non-technical executive leadership.
- Partner with internal engineering teams to refine optimization algorithms, ensuring that our models remain scalable and responsive to evolving industry demands.