• Lead day-to-day execution of the Large Form Factor MDC product line, with accountability for delivery • Execute against the segment strategy set with the GM of Form Factors, ensuring alignment with Armada's broader platform and growth objectives. • Establish operating rhythms, KPIs, and accountability mechanisms to drive predictable execution. • Provide input to the GM on pricing, investment prioritization, capacity planning, and scaling strategy. • Lead end-to-end product development, including system architecture, mechanical/electrical design, thermal systems, integration, and certification. • Ensure designs are manufacturable, scalable, cost-optimized, and compliant with global standards (UL, IEC, NEC, ISO, etc.). • Drive standardization and modularity while maintaining flexibility to meet customer-specific requirements. • Balance innovation velocity with reliability, quality, and time-to-market. • Manage manufacturing operations for large-scale modular data center systems, including execution of factory strategy (internal and external), capacity scaling, and throughput optimization with partners. • Build and scale repeatable production processes, ensuring quality, schedule adherence, and cost control. • Partner with supply chain leadership on sourcing and execution for long-lead and critical components (power, cooling, steel, switchgear, IT infrastructure). • Implement strong quality management systems, root-cause analysis, and continuous improvement programs. • Drive operational readiness for rapid growth while maintaining delivery excellence. • Translate customer demand and pipeline signals into executable production, staffing, and capital plans. • Partner closely with Sales, Finance, Legal, Supply Chain, and Program Management to execute complex customer deployments. • Oversee contract execution, delivery commitments, risk management, and change control. • Drive scalable business processes across quoting, cost modeling, order management, and delivery. • Collaborate with and mentor peers across engineering, manufacturing, and operations to drive high performance. • Contribute to a culture of ownership, urgency, accountability, and operational excellence. • Support hiring efforts to bring in strong technical and operational talent for a world-class modular infrastructure product line.

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• Design, develop, and implement graph-based analytics solutions supporting fraud detection and investigative analysis. • Use graph databases and network analysis techniques to identify hidden relationships, patterns, and connections across entities. • Develop graph models representing individuals, organizations, transactions, accounts, programs, and other relevant entities. • Apply graph algorithms involving centrality, community detection, link analysis, path analysis, clustering, and anomaly detection. • Integrate graph analytics with machine learning, statistical analysis, and other advanced analytic methods. • Analyze structured, semi-structured, and unstructured data from public, non-public, and commercial sources. • Support entity resolution, identity matching, relationship mapping, and risk-scoring activities. • Develop and refine fraud-detection models, rules, and investigative use cases. • Collaborate with investigators and analysts to translate operational and investigative needs into graph analytics solutions. • Build visualizations, link charts, dashboards, and other work products that clearly communicate complex relationships. • Support the development, testing, validation, and deployment of graph analytics models and applications. • Evaluate model performance and recommend adjustments to improve accuracy, scalability, and usefulness. • Document methodologies, data sources, assumptions, model designs, findings, and limitations. • Participate in technical reviews, quality-control activities, and project demonstrations. • Present analytical findings and recommendations to technical and non-technical stakeholders. • Support the maintenance and improvement of deployed graph analytics solutions.

Role Description The Data Scientist applies advanced mathematical, statistical, and machine learning methods to operational problems drawn from freight and transportation networks—routing, network structure, utilization, demand and cost modeling, and prediction. This is an analytical role, not a data engineering or MLOps role; the focus is on formalizing ambiguous business questions, selecting and defending appropriate methods, and communicating findings and their limitations to operational and executive stakeholders. Graph-structured data is central to how the business is modeled, so comfort reasoning about networks is a distinct advantage. - Translate ambiguous operational problems into well-posed statistical, mathematical, or graph-theoretic questions - Design and run analyses including statistical modeling, regression, optimization, simulation, and predictive/ML modeling - Build and validate predictive models, and clearly characterize where they generalize and where they do not - Work directly with real data—cleaning, exploring, and interrogating it before modeling - Communicate methods and results to operational and executive stakeholders, including the reasoning behind methodological choices and their limitations - Distinguish correlation from causation and signal from artifact, and state clearly when the data cannot answer the question Qualifications - STEM degree required; Master's or PhD in a quantitative field (statistics, applied math, operations research, physics, computer science, or similar) strongly preferred - 4+ years of applied analytical or data science experience (mid–senior) - Strong foundation in statistics, probability, and applied mathematics (linear algebra, optimization, or similar) - Experience with predictive modeling and machine learning, and the judgment to know when a simpler method is the right one - Proficiency scripting in Python or R for analysis—clean, correct code, without an expectation of shipping production systems - Fluency with data manipulation (SQL, pandas/dplyr, or equivalent) - Ability to reason about uncertainty and clearly state assumptions and their consequences - Demonstrated ability to explain technical work to non-technical audiences - Graph/network analysis (community detection, flow, shortest-path, centrality) or graph-based ML - Time series, causal inference, or experimental design - Optimization or operations research applied to logistics, routing, or scheduling - Domain exposure in trucking, freight, logistics, or supply chain Benefits - Thrive in a supportive team that provides coaching and training to help develop your skills and progress your career - Dispersed work environments that promote a healthy work-life balance - Meaningful and impactful work and projects with an essential service provider - Join our engaging Wellness Program & extracurricular sports teams Company Description - Celebrating over 50 years in Business - Active in giving back through Corporate Social Responsibility and Charitable Giving - Committed to environmental sustainability Bison Transport is committed to Diversity and Inclusion in the Workplace.