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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Analyst - **Company:** BDP International - **Location:** Ocala, FL, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Microsoft Azure, Cloud Database, Software Documentation, R (Programming Language), Python (Programming Language), Machine Learning, Network Planning and Design, Power BI, Tensorflow, SQL Databases, Tableau (Software), Unstructured Data, Azure Data Factory, Large Language Models, Snowflake, Apache Spark, Model Validation, Data Layers, Scikit Learn, Information Technology, Data Analytics, Software Version Control, Databricks - **Published:** September 17, 2026 - **Apply:** https://bdpinternational.mua.hrdepartment.com/hr/ats/Posting/view/8698 ## About the Role Bachelor's Degree, EDUCATION Bachelor's degree in Data Analytics, Computer Science, Statistics, Supply Chain, Industrial Engineering, or related quantitative field. Or equivalent work experience. YEARS OF EXPERIENCE 10+ years of progressive experience in data analytics, with at least 5 years focused on procurement, logistics, supply chain, or 4PL/Control Tower operations. Demonstrated track record building scalable analytical assets and setting standards in a senior IC capacity. REQUIRED SKILLS & COMPETENCIES * Advanced proficiency in SQL, Python, and modern analytics tooling (dbt, semantic layers, BI platforms such as Power BI, Tableau, or ThoughtSpot) with hands-on experience designing scalable, reusable data models. * Deep domain expertise across procurement and sourcing analytics - spend analysis, volume summaries, baseline freight cost modeling, RFQ/RFP analytics, scenario optimization, carrier and supplier performance measurement, and savings tracking across Ocean, Air, Road, and Rail modes. * Demonstrated experience leveraging AI tools (LLMs, copilots, ML libraries) to accelerate analytical workflows, automate routine reporting, and improve analyst and operational productivity at scale. * Proven ability to establish standards, best practices, and governance frameworks for analytics (data quality, model validation, documentation, version control) within a multi-client professional services or managed services environment. * Excellent communication and stakeholder management skills, with comfort presenting complex analytical findings and recommendations to Fortune 500 client executives and BridgeNet leadership. PREFERRED QUALIFICATIONS * Experience with TMS platforms (Xonar or equivalent), e-sourcing platforms (Keelvar or equivalent), and cloud data environments (Azure, Snowflake, or similar). * Prior experience supporting clients in a 4PL, Control Tower, or managed procurement/logistics services environment. * Relevant certifications such as CPSM, CSCP, CILT, or data/analytics certifications (e.g., dbt Analytics Engineer, Azure Data, Databricks). * Experience with applied data science principles within supply chain using tools such as R, Spark, TensorFlow. ## Description The Senior Data Analyst is an authority individual contributor responsible for elevating the analytical foundation of BridgeNet's managed procurement and 4PL Control Tower service offering. This role sets standards and best practices for procurement and supply chain analytics across the organization, designs scalable analytical models that can be reused across client engagements, and leverages modern tools to drive operational excellence in spend visibility, sourcing strategy, scenario optimization, and performance reporting. As a standards-setter and technical leader-by-example, the Senior Data Analyst partners with Account Management, Service Delivery, Business Analytics, and Supply Chain Engineering services to translate complex freight, spend, and operational data into decision-grade insights for both BridgeNet and client stakeholders by developing & employing scalable analytical solutions rooted in data science. 4. Key Responsibilities * Establish and own divisional standards, best practices, and reusable methodologies for procurement and sourcing analytics across BridgeNet's managed service offering. * Design, build, and maintain scalable, productized analytical models, semantic layers, and data products that can be deployed and reused across multiple client engagements with minimal customization. * Identify, evaluate, and operationalize AI and machine learning tools (LLM-assisted analysis, automated reporting, anomaly detection, predictive sourcing) to drive operational excellence and analyst productivity across the Control Tower service model. * Lead by example as the senior contributor, mentoring analysts across regions on advanced analytical techniques, code quality, model documentation, and the responsible use of AI in client-facing deliverables. * Develop advanced spend, freight, and supplier analytics - including spend cubes, lane and mode profiling, savings tracking, supplier scorecards, and what-if scenario models - that directly support sourcing strategy, network design, and continuous improvement. * Partner with Business Analytics, Supply Chain Engineering, Solution Architecture, and Technology teams to ensure analytical models integrate cleanly with Xonar (TMS), Keelvar (e-sourcing), client ERPs, and BridgeNet's dbt and semantic layer infrastructure. * Define and govern data quality, model validation, version control, and documentation standards for analytical assets used in client-facing reporting and executive business reviews. * Translate complex datasets and model outputs into clear, executive-grade narratives, visualizations, and recommendations for key client stakeholders, including QBR and stage-gate deliverables. * Lead discovery and onboarding for new client engagements from an analytics perspective - assessing data sources, defining the analytical operating model, and accelerating time-to-value with pre-built BridgeNet analytical assets. * Employ data science to support both structured and unstructured data analysis leveraging ML modeling & algorithms. * Contribute to BridgeNet's intellectual capital by codifying analytical playbooks, reference architectures, and benchmark libraries that strengthen the People, Process, and Technology pillars of the Control Tower operating model. 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