Lead Data Analyst

Key Responsibilities: Lead and mentor a team of data analysts to develop and maintain logistics data models and dashboards. Design and implement ETL processes to integrate data from multiple sources, including TMS, WMS, and ERP systems. Develop and optimize data models to support route optimization, fleet utilization, load balancing, and last-mile delivery performance. Create interactive dashboards and reports to provide actionable insights for executive decision-making. Collaborate with operations, transportation, and supply chain teams to identify key performance indicators (KPIs) and analytics opportunities. Establish and enforce data governance standards to ensure accuracy and integrity of logistics data. Drive predictive analytics initiatives for demand forecasting, fleet maintenance, and cost reduction strategies. Partner with IT, engineering, and business stakeholders to implement advanced analytics solutions and automation. Technical Skills: ETL Development: Expertise in Informatica, Talend, SSIS, or similar tools for data extraction, transformation, and loading. SQL Proficiency: Advanced SQL skills for querying large datasets and database optimization. Data Modeling: Experience in designing dimensional models and data warehouses tailored for logistics and supply chain operations. Visualization Tools: Hands-on experience with Power BI, Tableau, or QlikView to develop interactive analytics dashboards. Programming & Automation: Proficiency in Python or R for statistical analysis, machine learning, and automation. Logistics & Supply Chain Analytics Expertise Fleet Management Analytics: Utilization rates, fuel efficiency, predictive maintenance. Route Optimization & Transportation Network Analysis: Identifying cost-effective and time-efficient delivery paths. Warehouse Operations & Inventory Optimization: Monitoring stock levels and streamlining fulfillment processes. Last-Mile Delivery Performance: Real-time tracking, delivery time predictions, and exception management. Freight Cost Modeling & Spend Analytics: Analyzing cost structures and optimizing transportation spend. Supply Chain Visibility: End-to-end tracking and monitoring of shipments, orders, and compliance. Predictive Analytics: Forecasting demand, supply chain disruptions, and fleet availability. Preferred Tools & Technologies: Transportation Management Systems (TMS): SAP TM, Oracle TMS, JDA. Warehouse Management Systems (WMS): Manhattan, HighJump, SAP EWM. GIS & Location Intelligence: ESRI, Google Maps API for spatial analytics. Supply Chain Optimization Software: LLamasoft, Kinaxis for modeling and simulations. IoT Data Integration: Experience with telematics, RFID, GPS-based tracking systems. Leadership & Soft Skills 5+ years of experience in data analytics, with at least 2 years in a leadership role. Ability to translate business requirements into data-driven solutions. Experience managing end-to-end analytics projects, from conception to execution. Strong communication skills to present findings to both technical and non-technical stakeholders. Ability to prioritize multiple initiatives and align analytics efforts with business objectives.