Bachelor's degree in a quantitative discipline (Statistics, Mathematics, Economics, Data Analytics, Finance, or similar)
10+ years in commercial analytics, business intelligence, revenue/strategy analytics, or similar
5+ years leading and developing analytics teams
Strong foundation in applied statistics and quantitative methods
Advanced SQL skills with experience in relational/cloud databases
Proven ability to build executive-grade KPI dashboards in BI platforms
Director-level experience with large language model tools for analytics
Responsibilities
Define and own the commercial analytics and business-intelligence strategy
Establish best practices for analytics, reporting, and data governance
Partner with leadership to define KPIs and executive dashboards
Drive automation and scalability in reporting
Own recurring performance reporting for commercial accounts across diverse segments
Partner with Sales to run custom account-level analyses
Establish and own KPI dashboards for Remarketing Center Operations
Benefits
Collaborative work environment with a focus on continuous improvement
Opportunity to lead and impact analytics and BI strategy
Access to advanced analytics tools and technology platforms
Engagement with executive leadership for strategic decision-making
Exposure to a dynamic industry with growth opportunities
Full Job Description
The Commercial Analytics Director leads ACV's commercial intelligence function, turning data into decisions that grow revenue, strengthen customer relationships, and improve operational performance across our physical and digital channels. The ideal candidate pairs strong business acumen with genuine mathematical and statistical depth, fluency with databases and BI tooling, and the ability to translate complex analysis into clear stories for both executives and customers. A significant part of the role is customer-facing: partnering with Commercial Solutions and Sales to produce custom, account-level analyses that show existing and prospective commercial customers how remarketing vehicles upstream or downstream with ACV advances their own KPIs. Familiarity with the automotive wholesale and remarketing industry is a strong plus.
Key Responsibilities
Analytics Leadership & BI Strategy
Define and own the commercial analytics and business-intelligence strategy, aligning the analytics and BI roadmap with ACV's growth objectives.
Establish best practices for analytics, reporting, data visualization, and data governance across commercial functions.
Partner with executive leadership to define the KPIs and executive dashboards that guide strategic decisions.
Drive automation and scalability in reporting to reduce manual effort and speed time-to-insight.
Manage departmental priorities, budgets, and vendor relationships; foster a culture of curiosity and continuous improvement.
Commercial Account Reporting & Business Development Analytics
Own recurring performance reporting for commercial accounts across dealer, fleet, financial-institution, rental, OEM, and commercial-consignor segments.
Partner with Commercial Solutions and Sales to run custom, account-level analyses that quantify the value ACV delivers to each customer.
Demonstrate to existing and prospective commercial customers how remarketing vehicles upstream or downstream with ACV supports their KPIs - for example, days-to-sale, net proceeds and price retention, transportation and reconditioning costs, and channel mix.
Translate findings into compelling, executive-ready and customer-ready materials that support business development, renewals, and account expansion.
Develop customer segmentation and lifetime-value views that identify high-value accounts and growth opportunities.
Remarketing Center Operations - KPIs & Dashboards
Establish and own KPI dashboards for Remarketing Center Operations, giving leadership clear visibility into throughput, cycle time, inspection and condition quality, inventory flow, and cost-to-process.
Partner with operations leadership to define metrics, targets, and reporting cadences.
Surface bottlenecks and improvement opportunities that increase operational efficiency and vehicle liquidity.
Revenue, Pricing & Margin Analytics
Analyze auction pricing, buyer demand, conversion rates, and vehicle performance to support revenue growth.
Support pricing analytics across auction fees, digital services, transportation, reconditioning, and ancillary products, including elasticity and profitability considerations.
Monitor gross margin, revenue mix, and profitability across customer segments.
Advanced Analytics & Statistical Modeling
Apply sound statistical methods and, where appropriate, machine learning to improve commercial performance.
Develop predictive and segmentation models spanning:
Customer retention and churn
Revenue and demand forecasting
Vehicle pricing optimization
Inventory and buyer-propensity modeling
Sales opportunity scoring
Bring quantitative rigor and clear judgment to how models are built, validated, and communicated.
Cross-Functional Partnership
Finance - partner on budgeting, forecasting, and profitability analysis.
Sales & Commercial Solutions - measure territory and pipeline performance, acquisition, retention, and account growth.
Marketing - evaluate campaign performance and customer-acquisition costs.
Operations & Digital Product - improve auction efficiency, inventory flow, and marketplace optimization.
Qualifications
Required
Bachelor's degree in a quantitative discipline - Statistics, Mathematics, Economics, Data Analytics, Finance, or a related field.
10+ years in commercial analytics, business intelligence, revenue/strategy analytics, or a closely related field.
5+ years leading and developing analytics teams.
Strong foundation in applied statistics and quantitative methods (e.g., regression, forecasting, segmentation, experimentation, and statistical inference).
Advanced SQL, with hands-on experience working directly in relational and/or cloud databases and data models.
Proven ability to design and build executive-grade KPI dashboards in BI platforms such as Power BI, Tableau, or Looker.
Director-level experience leveraging large language model (LLM) tools (such as Claude) to develop an industry-leading suite of analytics and business-intelligence tools.
Strong financial and quantitative modeling skills.
Track record partnering with sales, pricing, or commercial organizations and presenting to executive leadership.
Ability to translate complex analysis into clear narratives for both executive and customer audiences.
Preferred
Master's degree (MBA, Analytics, Data Science, Statistics, Economics, or a related field).
Experience in automotive, wholesale vehicle auctions, remarketing, fleet management, mobility, retail automotive, or marketplace businesses.
Proficiency in Python or R for advanced analytics.
Familiarity with cloud data platforms such as Snowflake, Azure, AWS, or Google Cloud.
Experience with CRM platforms (Salesforce preferred).
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