Sr. Director Analytics & Data

United Site Services•Meridian, ID

About The Position

United Site Services is the industry leader in comprehensive site services, committed to creating partnerships that help enable our customers’ project and event success. Our deep industry expertise, excellence in process management, and dedication to corporate responsibility are pillars of our value proposition; each supported by tangible, best practice programs. Our success is fueled by the dedication and collaboration of our diverse team, which includes field technicians, customer care representatives, sales professionals and functional experts. Each member of our team plays a vital role in ensuring a seamless and reliable experience for our customers. By joining United Site Services, you will be part of an organization that values continuous improvement, teamwork, and excellence in every aspect of our business.

Requirements

Minimum 4 Year / Bachelors Degree in a quantitative field (Business, Economics, Engineering, Statistics, Data Science)
10+ of progressive analytics/data leadership experience
5+ years of managing teams
Demonstrated experience spanning at least three of the following domains: supply chain/operations, finance/FP&A, and marketing/commercial analytics.
Hands-on experience deploying AI/ML models into production, and a strong point of view on applying generative AI to business operations.
Proven ability to build analytics functions from the ground up and drive adoption with nontechnical executive stakeholders.
Demonstrated experience owning enterprise data strategy and governance, including data quality, master data management, and cross-functional data standards.
Strong SQL and experience with modern BI/analytics tools (e.g., Sigma, Power BI, Tableau, Looker) and data platforms (e.g., Snowflake, Databricks).
Sit while answering phones or reply to emails: Constant
Use hands and fingers to handle, control or feel objects tools or controls: Frequent
Repeat the same movements when entering data: Frequent
See details of objects that are less than a few feet away: Frequent
Understand the speech of another person: Frequent
Focus on one source of sound and ignore others: Frequent
Hear sounds and recognize the difference between them: Frequent
See differences between colors, shades and brightness): Frequent

Nice To Haves

MBA or advanced degree a plus
Experience in logistics-, field-services-, distribution-, or asset-intensive business is highly preferred.

Responsibilities

Own the enterprise analytics roadmap, aligning data and AI investments with USS's growth, margin, and customer experience priorities.
Build, mentor, and scale a team of analysts, data scientists, and analytics engineers.
Serve as a trusted advisor to the executive team, translating data into actionable strategic recommendations.
Establish governance, data quality standards, and a consistent framework for KPIs across departments.
Serve as the enterprise owner of data strategy, standards, and architecture - accountable for data as a shared, trusted company asset across all business units.
Own enterprise data governance, including data quality, lineage, master/reference data management, and stewardship roles across Operations, Finance, and Marketing.
Partner with IT/Engineering to define and maintain the enterprise data platform (warehouse/lakehouse), integration pipelines, and access controls.
Establish and enforce data policies for privacy, security, retention, and regulatory compliance in partnership with Legal and IT.
Define the single source of truth for core enterprise metrics and ensure consistent definitions and reporting standards company-wide.
Act as the executive escalation point for enterprise data quality, access, and infrastructure issues impacting business operations.
Lead analytics for fleet management, route optimization, service scheduling, inventory, and network/facility planning.
Develop demand forecasting and capacity planning models to support seasonal and regional service variability.
Partner with Operations leadership to identify efficiency opportunities in labor productivity, asset utilization, and last-mile logistics.
Build predictive maintenance and asset-lifecycle models for the equipment fleet.
Partner with FP&A on revenue analytics, margin analysis, pricing strategy, and cost-to-serve modeling.
Support M&A integration analytics, including synergy tracking and post-acquisition performance measurement.
Build dashboards and forecasting models that connect operational drivers to financial outcomes (EBITDA, unit economics, working capital).
Provide analytical support for budgeting, long-range planning, and board-level reporting.
Lead marketing mix, lead-generation, customer acquisition cost (CAC), lifetime value (LTV), and retention/churn analytics.
Enable segmentation and targeting models to support commercial growth and cross-sell/up-sell strategies.
Partner with Marketing and Sales to measure campaign ROI and optimize the customer funnel.
Champion the adoption of AI/ML and generative AI across the organization - from operational forecasting and route optimization to customer service automation and internal productivity tools.
Evaluate, pilot, and scale AI use cases with clear ROI, working closely with IT/Engineering on data infrastructure and MLOps.
Stay ahead of emerging AI capabilities (LLMs, agentic workflows, predictive/prescriptive analytics) and translate them into practical business applications.
Establish responsible-AI practices, including data privacy, model governance, and change management for AI adoption.