Senior Sales Strategy & Analytics Manager

United StatesRemoteFull-timesenior

DataData Manager

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Quick Summary

Requirements Summary

5+ years of experience in GTM analytics, sales operations, or a related function supporting an enterprise, multi-product go-to-market organization; B2B SaaS experience is strongly preferred.

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DataData Manager

The Senior Sales Strategy & Analytics Manager will help shape how a growing commercial organization plans, measures, and accelerates revenue performance. You will own critical elements of go-to-market planning, including ARR and pipeline targets, sales quotas, headcount and capacity models, and territory design. Working closely with GTM and Finance leadership, you will turn complex data into clear insights and actionable recommendations. You will build the dashboards, KPI frameworks, and analytical tools that help commercial teams identify risks and opportunities early. This is a senior individual contributor role combining hands-on analytics with strategic influence and executive-level communication. You will also use AI to develop scalable tools and workflow efficiencies that become part of day-to-day GTM operations. The role sits within a focused Sales Strategy & Analytics team dedicated to helping commercial leadership make data-backed decisions that support revenue growth.

Build company-wide annual ARR and pipeline generation targets by translating growth objectives into structured assumptions, scenarios, and planning models.
Own sales quota-setting processes, headcount and capacity models, and rep productivity analysis.
Support territory design to align commercial coverage with growth opportunities.
Establish consistent planning cycles by defining clear inputs, timelines, deliverables, and processes across workstreams.
Build and maintain dashboards, scorecards, and KPI reporting that provide sales, sales engineering, and xDR teams with clear visibility into performance.
Define leading indicators that identify emerging risks and opportunities before they impact topline results.
Standardize metrics across regions, channels, and product lines to create a reliable single source of truth.
Use AI to build practical GTM tools and workflow efficiencies that scale analytics capabilities and support daily commercial operations.
Partner with GTM and Finance leaders to shape performance measurement frameworks and decision-making processes.
Translate complex analysis into clear, defensible recommendations that senior leaders can act on.
Align stakeholders around consistent data narratives and resolve fragmented interpretations of business performance.
Establish high standards for analytical rigor, data quality, and quality assurance across the analytics function.
Mentor peers and junior analysts on modeling, scenario planning, analytical approaches, and executive communication.
Advance reporting automation and data quality as the organization and commercial operations scale.

Requirements

~2 min read

5+ years of experience in GTM analytics, sales operations, or a related function supporting an enterprise, multi-product go-to-market organization; B2B SaaS experience is strongly preferred.
Deep understanding of go-to-market motions, sales planning, territory design, quota setting, and forecasting for sales, sales engineering, and xDR functions.
Strong hands-on SQL skills, with the ability to independently pull, join, validate, and analyze data.
Fluency with modern B2B commercial technology, including platforms such as Salesforce, Gong, and Clari.
Experience with BI tools such as Tableau, Looker, Power BI, or similar platforms.
Practical experience using AI to build GTM tools and workflow efficiencies that are adopted and used at scale.
Strong executive communication skills, with the ability to distill complex analysis into clear recommendations for senior commercial leadership.
Strong judgment and structured problem-solving skills, particularly when working through ambiguous business challenges.
Confidence to challenge established assumptions and approaches when data supports a different direction.
Experience with dbt, Python or R, and cloud data warehouses such as Snowflake, BigQuery, or Redshift is a plus.
Experience building with LLM APIs or AI-assisted analytics tools, including natural-language querying or automated narrative reporting, is a plus.
Ability to work effectively in a remote environment and collaborate across commercial and finance functions.