Customer Analytics Manager

Abnormal AI, Inc.

$107K — $154K *
US-AnywhereRemote in United States
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in analytics, data science, or business intelligence, preferably in a SaaS environment supporting Customer Success or Revenue teams.
  • Advanced SQL skills and experience building data models using platforms like Snowflake, Databricks, or BigQuery.
  • Proficiency with BI/visualization tools like Sigma, Tableau, or Looker.
  • Proven ability to build and maintain effective customer health scoring models.
  • Experience developing product usage metrics from raw telemetry or usage data.
  • Demonstrated capability in identifying upsell, cross-sell, or expansion opportunities from existing customers.

Responsibilities

  • Build and maintain the customer health scoring model to reflect risk and satisfaction indicators.
  • Develop data models for product usage and adoption for visibility into customer engagement.
  • Conduct deep-dive data analysis for CS leadership, translating findings into actionable insights.
  • Create metrics to assess product configuration in relation to best practices.
  • Identify growth opportunities such as upsell and cross-sell within the customer base.
  • Collaborate with cross-functional teams to maintain consistent analytics definitions.
  • Present data insights and recommendations to leadership in a clear format.

Benefits

  • Comprehensive benefits package.
  • Eligibility for bonuses or incentives and equity stakes.
  • Possibility of flexible work arrangements.
Full Job Description
About the Role

Abnormal AI is looking for a Customer Analytics Manager to join our CS Operations team. This role owns the data models and analytics that let us understand, score, and grow our customer base - from health scoring and product usage/adoption to expansion opportunity sizing. You'll partner closely with Customer Success, Sales, and Product leadership to turn raw usage and configuration data into models and insights that drive proactive, revenue-relevant action. The ideal candidate is equally comfortable in the technical weeds of a data model and in a room with executives, translating complex analysis into a clear, actionable narrative.
What you will do
  • Build and maintain the customer health scoring model, ensuring it reflects risk, engagement, and satisfaction signals across the customer lifecycle.
  • Develop and own data models for product usage and adoption, giving CS, Support, and leadership clear visibility into how customers engage with the platform.
  • Conduct ad-hoc, deep-dive data analysis for CS leadership, Sales, and Product, translating findings into clear, actionable recommendations.
  • Build and maintain product configuration metrics that surface how customers have deployed the platform relative to best practice.
  • Identify and model upsell, cross-sell, and expansion addressable market opportunities within the existing customer base.
  • Partner cross-functionally with CS Operations, Sales, Product, and Data teams to keep analytics infrastructure and definitions consistent and trusted.
  • Present insights and recommendations to CS leadership in a clear, decision-ready format.

Must Haves
  • 5+ years of experience in analytics, data science, or business intelligence, ideally supporting a Customer Success or Revenue org at a SaaS company.
  • Advanced SQL skills and hands-on experience building data models in a modern data warehouse (e.g., Snowflake, Databricks, BigQuery).
  • Proficiency with BI/visualization tools such as Sigma, Tableau, or Looker.
  • Proven experience building and maintaining customer health score models that drive proactive action across CS teams.
  • Experience building product usage/adoption or product configuration metrics from raw product telemetry or usage data.
  • Track record of identifying and sizing upsell, cross-sell, or expansion opportunities within an existing customer base.
Nice to Have
  • Experience with Customer Success tools such as Gainsight, Gong, or Pendo.
  • Hands-on experience building AI-powered workflows (e.g., Glean agents, Claude skills) to automate analysis.
  • BS/BA degree in a quantitative field (Statistics, Economics, Computer Science, or related).

#LI-ME1

Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location.
In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package.

Base salary range:

$107,100-$154,000 USD

AI and our hiring process
Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and identify areas for the interviewer to explore. They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person.

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