GTM Strategy and Operations Associate – Automation & AI

LinkedIn•New York, NY

3d•$84,000 - $137,000•Hybrid

About The Position

This role will be based in San Francisco or New York. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. The GTM Innovation Hub builds the tools, automation, and analytical systems that LinkedIn Talent Solutions Sales Operations runs on. We partner with Sales Ops, CRM, and Analytics teams to design and scale data-driven workflows for forecasting, planning, segmentation, and quota setting. This is not a traditional Sales Operations role. We're hiring builders who pair technical depth with business judgment — people who can take an ambiguous GTM problem, translate it into a structured analytical or technical solution, and ship something that gets used. As a GTM Strategy and Operations Associate, you will design, build, and operationalize the systems that move the organization from manual, ad hoc analysis to repeatable, automated workflows that scale across regions and segments.

Requirements

BA/BS in a quantitative or technical field (Computer Science, Engineering, Data Science, Analytics, Economics, Business, or similar) — or related equivalent experience.
2+ years of experience in a strategic, analytical, or operational role (e.g., Sales Operations, Business Operations, Consulting, Finance, Analytics).
2+ years of experience building automations workflows or data tools in a professional setting, with real users and real stakes.
1+ years of experience of hands-on experience with at least one LLM API (OpenAI, Anthropic, Google, etc.) — including prompt engineering, tool use / function calling, etc.
1+ years of experience with Python for building and integrating tools and APIs.
2+ years of experience of SQL and excel for analysis and prototyping.
2+ years of experience working directly with business stakeholders — scoping ambiguous asks, gathering requirements, presenting work-in-progress, and incorporating feedback. Comfortable contributing in meetings with senior leaders, even if you don't run them

Nice To Haves

Experience in a GTM, Sales, Revenue, Finance, or operations-adjacent context — Sales Ops, Rev Ops, Analytics Engineering, technical consulting, or strategy roles with a heavy build component.
Working understanding of core Sales/GTM concepts: quota setting, territory design, pipeline coverage, forecasting, or incentive compensation.
Familiarity with CRM and planning systems (D365, Salesforce, Anaplan) as both business systems and integration targets.
Experience automating end-to-end workflows that move data and trigger actions across multiple systems.
Experience building with agentic frameworks,
Familiarity with modern data tooling (e.g., dbt) for transforming and modeling analytical data.
Evaluation mindset — ability to define success metrics for AI tools and build lightweight evals to track quality over time.
Experience surfacing outputs via dashboards (BI tools or code-built) and building executive-ready narratives around what the data shows.

Responsibilities

Diagnose before you build — work directly with Sales, Finance, and GTM stakeholders to understand root causes and prioritize problems by business impact before deciding what to build.
Build and ship AI-powered tools — design, develop, and deploy LLM-powered applications, agents, and internal tools that solve real GTM problems across forecasting, quota setting, territory planning, segmentation, and performance reporting.
Automate workflows end-to-end — identify high-value manual processes and replace them with reliable, production-grade automations.
Build data pipelines and surface insights — design lightweight pipelines that move and transform operational data; perform deep-dive analyses on large datasets (CRM, financial, customer) to identify leading indicators, risks, and opportunities.
Partner closely with stakeholders — run discovery on specific problems with Sales, Finance, and GTM teams; clarify scope; demo work-in-progress; incorporate feedback. Build trust through reliable delivery.
Communicate clearly across audiences — explain technical trade-offs in plain business language; make the case for what you're building (and what you're not) with both peers and senior leaders.
Document and scale your work — write clear documentation so others can maintain, extend, and learn from what you build; support adoption across Sales and Operations partners.