Data Analyst | Customer Journey & Attribution

Description

The company makes technology that helps public safety agencies and enterprises protect people and places, and this team makes sure customers get real value from it.

The customer success group helps agencies and enterprises adopt the software, use it in daily operations, and renew over the long term.

Customer success advisors act as trusted guides on advanced use cases and multi-year partnerships, backed by data and product knowledge.

This is a hands-on individual contributor role for a data analytics manager who tracks performance across digital customer lifecycle touchpoints and one-to-one customer success work.

You will measure how automated emails and in-app triggers work alongside direct customer success manager interventions to speed up time-to-value, improve retention and grow revenue.

You will be the data partner for the campaign strategy, product insights and customer success operations teams.

Responsibilities

• Build, maintain and refine multi-touch attribution models that measure the separate and combined effect of adoption work, digital touchpoints and advisor interventions, including links to product usage and retention.
• Create data pipelines that connect digital engagement data, such as email opens, in-app triggers, product usage and event attendance, with Gainsight call-to-action outcomes, logged meetings and CRM lifecycle stages.
• Tie early adoption measures like time-to-value, active usage and feature adoption to long-term results: net revenue retention, expansion revenue and customer retention.
• Give customer success leadership and campaign strategists data-based advice on intervention thresholds, call-to-action targeting and playbook messaging.
• Work with campaign strategy and product insights to segment customers by behavior and usage, and refine trigger logic for automated campaigns and Gainsight call-to-actions.
• Find where drop-offs and slow conversions stall digital engagement, and where targeted intervention gives the biggest lift.
• Find, clean, transform and organize messy data from many sources into reliable datasets.
• Work with product insights and customer success operations to unify identity resolution, tag hygiene and user event logging across the post-sale journey.
• Build clear, reliable dashboards in Tableau or Looker that show campaign performance, attribution splits and channel efficiency.
• Use AI tools such as Claude to speed up SQL writing, scripting, data cleaning and complex analysis.

Requirements

• Legal authorization to work in the U.S. indefinitely is required. Employer work permit sponsorship is not available for this position.
• Preferred: 5+ years in data analytics, marketing analytics or revenue or customer success operations, including at least 2 years on attribution modeling or lifecycle analytics in SaaS.
• Preferred: a track record as a hands-on individual contributor with a strong business operations background, able to balance complex technical data work with practical problem solving.
• Preferred: you must be a US citizen and currently live in the United States.
• Preferred: direct hands-on experience building multi-touch attribution models with SQL, Python or R.
• Preferred: advanced SQL and hands-on work with Snowflake, BigQuery or Redshift.
• Preferred: experience building clear, working dashboards in Tableau, Looker or Power BI.
• Preferred: familiarity or hands-on experience with Gainsight, Salesforce or HubSpot.
• Preferred: proven ability to clean and organize messy data from many sources into unified datasets for identity resolution and event tracking.
• Preferred: ability to explain complex analysis and multi-touch models to campaign strategy, product insights and CS Ops stakeholders in clear, actionable terms.
• Preferred: hands-on use of AI tools such as Claude, ChatGPT or Copilot for analysis, SQL, data preparation and scripting.
• Preferred: deep experience linking digital engagement with Gainsight call-to-action outcomes, meeting events and CRM lifecycle stages.
• Preferred: deep knowledge of early SaaS metrics and how they correlate with NRR and expansion revenue.

Conditions

Target base salary is $100,000 to $125,000 USD.

Pay within the range depends on job-related knowledge, skills and experience, and the final offer depends on the individual candidate.

Travel is under 10%.

No relocation is provided.

This is an experienced-level position.

Benefits

• Incentive bonus plans.
• Medical, dental and vision coverage.
• Company-matched 401K.
• 10 paid holidays.
• Generous PTO packages.
• Stock purchase plan for employees.
• Parental and family leave, paid.
• A referral payment plan is offered.
• The company lists further benefits beyond these.