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.
- 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.
- 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).
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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.
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.
Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.
Skills Required
- 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.
- 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.
- 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).
Abnormal Security Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Abnormal Security and has not been reviewed or approved by Abnormal Security.
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Fair & Transparent Compensation — Pay is considered aggressively benchmarked to leading tech markets with annual reviews, and feedback suggests engineering and sales roles are compensated competitively with strong upside potential.
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Healthcare Strength — Health coverage is portrayed as robust, including employer-paid premiums for employees in prior postings, One Medical access, and globally designed healthcare and parental leave.
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Leave & Time Off Breadth — Time off provisions include flexible/unlimited PTO, company holidays, and paid parental leave that the company positions as globally available.
Abnormal Security Insights
What We Do
The Abnormal Security platform protects enterprises from targeted email attacks. Abnormal Behavior Technology (ABX) models the identity of both employees and external senders, profiles relationships and analyzes email content to stop attacks that lead to account takeover, financial damage and organizational mistrust. Though one-click, API-based Office 365 and G Suite integration, Abnormal sets up in minutes and does not disrupt email flow. Abnormal Security was founded in 2018 by CEO Evan Reiser, CTO Sanjay Jeyakumar, Head of Machine Learning Jeshua Bratman, and Founding Engineers Abhijit Bagri and Dmitry Chechik. The team previously built behavioral profiling and machine learning technologies at Twitter, Google and Pinterest that are being applied to solve a problem that costs organizations $1 billion per year, according to the FBI. The Abnormal Security platform stops targeted phishing, business email compromise and account takeover attacks that have never been seen before.
