Fluidra is looking for a Senior Data Analyst to join our team in Carlsbad, CA. WHAT YOU WILL CONTRIBUTE The Senior Data Analyst reports to the EVP of Manufacturing, Operations & Supply Chain and is responsible for turning operational data into actionable business insights across Fluidra’s North American operations. This is a business-facing role focused on analysis, interpretation, and executive communication rather than building data infrastructure. Leveraging an established SQL Server environment and support from technical resources, the role delivers executive-ready dashboards, predictive models, and AI-driven insights to improve forecasting, inventory health, and overall supply chain performance. The position operates with high autonomy and ownership and works closely with executive leadership, plant managers, supply chain teams, and the corporate Data & Analytics group. Additionally, you will: Business Analytics & Executive Communication Coordinate and partner with Plant Managers and Supply Chain leaders on analytical reviews and monthly/quarterly business reviews. Transform complex operational data into compelling executive presentations with clear narratives and actionable recommendations. Challenge assumptions and bring a business mindset to data interpretation — not just report what happened, but explain why and what to do next. Develop and manage executive dashboards covering manufacturing throughput, conversion productivity, cost efficiency, inventory health, booking/shipping/backlog, fill rate, OTIF, and logistics KPIs. Serve as the analytical voice in leadership meetings, driving decisions through data. Advanced Analytics, Predictive Modeling & AI Leverage existing SQL Server infrastructure to build predictive models for demand, inventory, freight, capacity planning, and cost to serve. Conduct scenario modeling to quantify cost–service–risk trade-offs and support strategic decisions. Use AI/ML and automation to streamline recurring reporting and improve analytical speed and accuracy. Identify anomalies, emerging risks, and improvement opportunities across the supply chain. Manufacturing & Operations Analytics Partner with Plant Managers to analyze and improve Conversion Productivity, OEE, labor efficiency, scrap and yield variances, throughput stability, and service levels. Lead analytical deep dives to understand root causes of excess & obsolete inventory and operational inefficiencies. Support productivity initiatives through robust data analysis, financial modeling, and operational insights. Present findings to plant leadership with clear recommendations and follow-up actions. Supply Chain, Logistics & Distribution Analytics Analyze freight and transportation costs (carriers, lanes, modes), identify savings, and support contract decisions. Track distribution performance: cost per unit/order, carrier reliability, on-time delivery, and network flow. Support Distribution Centers with labor analytics, warehouse productivity models, and space optimization. Build total landed cost models by SKU, channel, and region. Demand, Forecasting & S&OP Support Measure forecast accuracy (MAPE, bias, error decomposition) and identify drivers of variance. Analyze seasonal demand patterns and support capacity/inventory positioning strategies. Partner with the Demand and Supply Planning teams to design and deliver monthly Demand reporting. Strengthen S&OP through consistent KPI reporting and data harmonization. Support working capital optimization through inventory analytics. Data Infrastructure & Tools Leverage and enhance existing SQL Server databases and data models. Design and maintain Power BI and Tableau dashboards used by leadership and operational teams. Work with the technical team to integrate data across ERP (Oracle, Epicor), WMS, and TMS environments. Develop Python scripts for automation, advanced analytics, and machine learning applications. Cross-Functional Collaboration Serve as an analytical partner to Operations, Finance, Supply Chain, IT, and Distribution leaders. Coordinate with the corporate Data & Analytics team on technical requirements and data governance. Ensure KPI alignment and data consistency across functions and systems. Train operational teams on self-service analytics tools and build data literacy.
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees