Apollo.io - Analyst, GTM Customer Intelligence

• 3+ years of experience in an analytics, Customer Success Operations, or Revenue Operations role, with direct exposure to post-sales data in a B2B SaaS environment. • Familiarity with CS data domains—health scoring, NRR, churn, renewal pipelines, support metrics, and customer lifecycle stages. You don't need to have built all of these from scratch, but you should understand what they are and why they matter. • Strong SQL skills and experience working with BI tools (e.g., Looker, Tableau, or similar). Able to build and own dashboards independently. • Experience with Salesforce or a CS platform (Gainsight, Vitally, ChurnZero, or similar). Understanding of how CS data is captured and where the quality gaps tend to live. • A translator's instincts. You know how to take a retention question from a CS VP and convert it into a clean, scoped analytics project—and you know when and how to push back on scope. • Analytically rigorous and detail-oriented. Post-sales data is messy—billing records, support tickets, and CRM data rarely agree out of the box. You need to enjoy untangling it and managing the organization’s expectations. • Comfortable operating across functions—you'll work with CS, CS Ops, Finance, Data Engineering, and occasionally Sales, and you need to collaborate effectively with all of them. • This role is ideal for an analyst or technical ops professional looking to deepen their exposure to analytics, intelligence, and data infrastructure, with a focus on the customer lifecycle. • AI Fluency & Tooling • Apollo operates at the intersection of AI and go-to-market, and our analytics team is expected to lead from the front. This role requires genuine fluency in leveraging AI tooling. That means: • Using LLMs as an active part of your analytics workflow. Whether it’s generating and debugging SQL, summarizing customer health scores, renewal forecasts, or retention signals, or accelerating the build of dashboards and documentation—you should be reaching for AI tools wherever they can accelerate the completion of tasks • Using LLMs as an active part of your analytics workflow. • Structuring and exposing data for AI interpretation. Understanding how to make customer health, retention, and post-sales data clean, well-labeled, and accessible so that AI tools can reason over it reliably. This includes thinking about schema design, field definitions, and semantic documentation. • Structuring and exposing data for AI interpretation. • Accelerating output with AI-assisted development. Using AI to compress the time from question to answer. We expect analysts at this level to leverage AI to raise their own output ceiling. • Accelerating output with AI-assisted development. • Staying current as the tooling evolves. The AI tooling landscape is moving fast. We want analysts who are curious, self-directed learners—people who experiment, share what works, and help raise the floor for the whole team. • Staying current as the tooling evolves. • Navigating AI’s limitations and pitfalls. Understanding where AI-generated outputs can introduce errors, bias, hallucinations, or false confidence, and implementing validation processes to ensure analytical rigor. You know when to trust AI, when to verify its work, and when to rely on first-principles analysis instead. • Navigating AI’s limitations and pitfalls. • The listed Pay Range reflects the total cash compensation inclusive of annual base salary and annual bonus as applicable. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonus target and annual base salary for the role. This salary range may be inclusive of several career levels at Apollo and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. Applicants interested in this role who are not located in the US may request the annual salary range for their location during the interview process. • Additional benefits for this role may include: equity; company bonus or sales commissions/bonuses; 401(k) plan; at least 10 paid holidays per year, flex PTO, and parental leave; employee assistance program and wellbeing benefits; global travel coverage; life/AD&D/STD/LTD insurance; FSA/HSA and medical, dental, and vision benefits. • Tier 1 Pay Range (San Francisco, New York City, Seattle) • $145,800—$182,200 USD • Tier 2 Pay Range (All other US Locations) • $126,700—$158,400 USD • We are AI Native • Apollo.io is an AI-native company built on a culture of continuous improvement. We’re on the front lines of driving productivity for our customers—and we expect the same mindset from our team. If you're energized by finding smarter, faster ways to get things done using AI and automation, you'll thrive here.