Senior Manager, Sales Analytics

CarGurus•Boston, MA
•$156,000 - $196,000•Hybrid

About The Position

CarGurus is seeking a Senior Manager of Sales Analytics to lead the team responsible for data, tools, and analysis supporting Sales and Customer Success across the US, Canada, and the UK. Reporting to the Senior Director of Pricing, Packaging & Analytics, this role guides the team, oversees key go-to-market data assets, and helps Sales leaders understand how team structure and sales activity affect retention and net MRR. The role expands analytics support beyond sales representatives to managers and leadership, strengthens data foundations through a modern, version-controlled stack, and develops applications for new data sources, including sales conversation transcripts. The Senior Manager leads a multi-level analytics team while remaining close to technical work, sets standards for analysis and data modeling, develops talent, and partners with Sales leaders to turn business questions into practical tools and analysis. The position leads business intelligence for Sales and Service; evaluates sales behaviors and go-to-market initiatives; modernizes the data stack; develops call-transcript data models and use cases; and stewards Sales data across Revenue. CarGurus offers a flexible hybrid model and a comprehensive Total Rewards Package.

Requirements

  • At least 8 years of experience in analytics, sales or revenue analytics, business intelligence, or analytics engineering.
  • At least 3 years leading analytics teams, including managers or senior individual contributors, with experience developing people and building career paths.
  • Expert SQL and strong data modeling skills, including the ability to review and troubleshoot others' work.
  • Hands-on experience with Snowflake or a similar cloud data warehouse, dbt, and Git-based development.
  • Experience leading a shift from ad hoc or view-based logic to tested, version-controlled models.
  • Experience working with unstructured or semi-structured data, such as conversation intelligence, call transcripts, or text, and using LLM or NLP techniques to structure and analyze it.
  • Strong knowledge of Salesforce data structures and sales processes.
  • Experience with enterprise BI tools such as Salesforce CRM Analytics, Omni, Looker, or Tableau.
  • Understanding of recurring-revenue metrics, including MRR, churn, retention, expansion, pipeline, and conversion, and how sales coverage and behavior influence them.
  • Strong executive communication skills, including the ability to frame decisions and help senior Sales leaders act on analysis.
  • A builder's mindset and experience creating self-serve tools and durable data assets while setting clear priorities for the team.

Nice To Haves

  • Experience in a SaaS, marketplace, or subscription business.
  • Python experience.
  • Experience using AI coding tools to accelerate analytics development.
  • Familiarity with automotive retail or dealer software.

Responsibilities

  • Lead analysts across Boston and Dublin, including a first-line manager and a Principal Sales Data Analyst; set goals, coach and manage performance, and support career development.
  • Establish clear career paths for analysts and managers.
  • Recruit, hire, and onboard team members as the team's scope evolves.
  • Set the team's operating cadence, intake process, and quarterly roadmap, making priorities and tradeoffs clear to stakeholders.
  • Oversee dashboards, hubs, and analytics applications used by Sales representatives, Account Managers, Product Specialists, and Dealer Performance Partners across the US, Canada, and the UK.
  • Improve manager and leadership visibility into churn and cancellations, book-of-business health, coverage and activity, and team effectiveness.
  • Partner with Sales Enablement and Sales leadership to support adoption and use of the team's tools.
  • Analyze how coverage models, team structures, engagement programs, and sales activity relate to retention, expansion, and net MRR.
  • Build repeatable measurement approaches for initiatives such as product launches, engagement programs, and coverage pilots.
  • Present findings in QBRs and planning sessions, connecting analysis to decisions and actions for Sales leaders.
  • Lead migration of transformation logic from manually maintained Snowflake views to dbt models and Git-based workflows, with code review, testing, documentation, and clear ownership.
  • Set guidance for when logic should be productionized in dbt versus maintained in a team sandbox, partnering with Data Platform Engineering and Analytics Engineering on standards, deployment, and lineage.
  • Reduce maintenance burden and key-person risk by consolidating duplicated or legacy objects and moving durable logic into documented, tested models.
  • Ensure the team can maintain and operate the solutions it builds.
  • Own modeling of Gong conversation data in Snowflake, including calls, participants, and transcripts, and connect it with Salesforce activity and account data.
  • Identify and deliver useful applications for transcript data at scale, including churn and save signals, competitor and pricing mentions, objection patterns, talk-track effectiveness, and inputs to coaching or AI agents; apply LLM-based extraction where appropriate.
  • Establish quality, governance, and appropriate-use standards for conversation data in partnership with Legal, Data Engineering, and Sales leadership.
  • Steward Sales-facing data and partner with Revenue Operations and Enterprise Applications to improve Salesforce data quality.
  • Integrate and model new go-to-market data assets, such as third-party marketplace data, for use across the analytics community.
  • Support development of a semantic layer for sales data assets to enable AI transformation use cases for analysts and sellers.
  • Act as an analytical center of excellence to enable analytically driven functions across the Revenue organization.

Benefits

  • Equity for all employees, both when they start and as they continue to grow with the company.
  • Career development programs.
  • Corporate giving programs.
  • Employee resource groups and communities.
  • Flexible hybrid model.
  • Robust time-off policies.
  • Daily free lunch.
  • New car discount.
  • Meditation and fitness apps.
  • Commuting cost coverage.
  • Comprehensive Total Rewards Package.
  • May qualify for discretionary bonuses or incentives and Restricted Stock Units (RSUs).
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