Data Analyst | Customer Journey & Attribution

Motorola Solutions•New York, NV

1d•$100,000 - $125,000

About The Position

Motorola Solutions is seeking a practical, data-driven Data Analytics Manager to lead performance tracking and analysis across digital customer lifecycle touchpoints and one-to-one Customer Success efforts. This hands-on individual-contributor role gathers, interprets, and applies data to enable teams and demonstrate the impact of their work. It measures how digital touchpoints, such as automated emails and in-app triggers, work alongside direct Customer Success Manager interventions to drive faster time-to-value, account retention, and revenue growth. The role partners with Campaign Strategy, Product Insights, and CS Operations teams to build attribution models, connect engagement data with customer success and CRM outcomes, analyze customer segments and journey bottlenecks, and provide actionable recommendations. It also involves cleaning and organizing data from disparate systems, improving identity resolution and event logging, building dashboards, and using AI tools to accelerate analytical work.

Requirements

At least 5 years of experience in data analytics, marketing analytics, or Revenue/CS Operations, including at least 2 years focused on attribution modeling or lifecycle analytics in SaaS.
Proven experience as a hands-on individual contributor with a strong Business Operations background and the ability to combine technical data work with practical operational problem-solving.
Must be a U.S. citizen and currently reside in the United States.
Direct, hands-on experience building multi-touch attribution models using SQL, Python, or R.
Advanced SQL skills and hands-on experience with Snowflake, BigQuery, or Redshift.
Ability to build clear, functional dashboards using Tableau, Looker, or Power BI.
Familiarity or hands-on experience with Gainsight, Salesforce, or HubSpot.
Demonstrated ability to clean, transform, and organize messy data from disparate sources into unified, reliable datasets for identity resolution and event tracking.
Ability to translate complex analytical concepts and multi-touch models into clear, actionable insights for business stakeholders.
Legal authorization to work indefinitely in the United States; employer work permit sponsorship is not available.

Nice To Haves

Hands-on experience using AI tools such as Claude, ChatGPT, or Copilot to accelerate analytical tasks, SQL query writing, data preparation, and scripting.
Deep experience connecting hybrid digital engagement metrics, including in-app triggers and email engagement, with Gainsight CTA outcomes, meeting events, and CRM lifecycle stages.
Deep familiarity with early-stage SaaS metrics such as time-to-value, active usage, and feature adoption, and their relationship to net revenue retention and expansion revenue.

Responsibilities

Design, maintain, and iterate on multi-touch attribution models to quantify the separate and combined impact of adoption efforts, digital touchpoints, and human Customer Success interventions, and analyze their relationship with product usage and retention.
Establish data pipelines connecting digital engagement metrics—including email opens, in-app triggers, product usage, and event engagement—with Gainsight CTA outcomes, logged meeting events, and CRM lifecycle stages.
Connect early-stage adoption metrics such as time-to-value, active usage, and feature adoption to net revenue retention, expansion revenue, and customer retention.
Provide CSA leadership and Campaign Strategists with data-backed recommendations to refine intervention thresholds, CTA targeting rules, and playbook messaging.
Partner with Campaign Strategy and Product Insights to identify customer segments and usage patterns and refine automated campaign triggers and Gainsight CTAs.
Analyze drop-off points and conversion velocity across campaign workflows to identify where digital engagement stalls and where targeted intervention can create incremental lift.
Find, clean, transform, and organize data from disparate sources into reliable datasets.
Partner with Product Insights and CS Ops to unify identity resolution and standardize tag hygiene and user event logging across the post-sale customer journey.
Build clear, reliable dashboards using Tableau or Looker to show campaign performance, attribution splits, and channel efficiency.
Use AI tools to accelerate SQL writing, scripting, data cleaning, and complex analysis.