GTM Analytics & Strategy
Analyzes GTM data across sales, pipeline, and operations to drive strategy, growth levers, and performance insights. Partners with leadership using SQL, BI tools, and Salesforce to deliver dashboards and recommendations. Requires 5+ years in analytics.
About the job
Responsibilities
- Develop a deep understanding of Shepherd's business model, GTM motion, and operating cadence to support data-driven decision-making
- Lead analytical deep dives on core GTM and business questions, identifying patterns, risks, and opportunities across pipeline, conversion, and performance
- Identify, develop, and maintain key performance indicators to measure GTM health, efficiency, and revenue growth
- Create and own dashboards and reports using SQL and BI tools to support leadership and functional teams
- Support internal and external reporting requirements, including executive, board, and partner-facing analyses
- Understand and meet key stakeholders' ongoing analytics needs and deliver actionable, data-driven recommendations
- Design and analyze experiments to test hypotheses and identify scalable growth levers (e.g., activities, segmentation, capacity allocation, GTM prioritization)
- Maintain, optimize, and establish best practices for BI and GTM tooling
- Ensure data quality and integrity through robust validation and QA processes
Requirements
- 5+ years of experience in analytics, business intelligence, data science, management consulting, or a related field
- Bonus: experience with revenue, sales, or GTM analytics in a high-growth environment
- Strong proficiency in SQL (required); experience with Python is a plus
- Advanced Excel skills and experience with modern BI and data visualization tools
- Experience analyzing and synthesizing data across Salesforce (CRM) and GTM tooling (e.g., Outreach) to inform pipeline strategy and execution
- Experience supporting GTM performance management, including quota setting and sales performance tracking
- Excellent communication skills, with the ability to clearly articulate insights and business implications to technical and non-technical audiences
- A high bar for accuracy, rigor, and polish in analytical work
- Strong business acumen and comfort operating in ambiguity
- Proven ability to prioritize effectively and manage multiple workstreams in a fast-paced environment
- A collaborative, low-ego mindset and experience working cross-functionally
Skills
SQL, Python, Excel, Salesforce, Outreach, BI Tools, Data Visualization, Tableau, Looker
Similar jobs
Data Analytics jobs
OnePay
United States
Own product and customer analytics across financial product experiences, turning behavioral data and customer feedback into roadmap recommendations and business decisions. The role requires 4–8 years of analytics experience, advanced SQL, strong analytical judgment, and daily fluency with AI-powered tools.
Idme
Mountain View, CA
Analyzes and improves enterprise marketing systems, campaign data, automation workflows, and experimentation programs. The role requires 5–10 years of marketing systems experience, hands-on Marketo and Salesforce expertise, strong reporting and stakeholder-consultation skills, and a bachelor's degree or equivalent experience.
Discord
United States
Own fraud detection, payments operations, investigations, and risk strategy while leading cross-functional programs and launch assessments. The role requires 4+ years in payments, fraud, or risk operations, strong SQL and card-network expertise, and the ability to communicate decisions across technical and business teams.
Eve
San Francisco, CAOwn growth and product analytics for activation, retention, expansion, and monetization, using experiments, SQL, AI automation, and product analytics tools. The role partners cross-functionally to turn insights into pricing improvements, product changes, and shipped growth initiatives.
Spade
New York, NY
Analyzes transaction enrichment performance, investigates data-quality anomalies, and builds dashboards and monitoring to improve product accuracy and reliability. Requires 3–5 years of analytical experience, strong SQL and Python, and experience with BI and automated alerting.