Commercial Analytics Director

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).

Originally posted on Himalayas