ZipRecruiter

Log In

1

Customer Acquisition Data Analyst Jobs (NOW HIRING)

IntelliPro Group Inc.

Business Data Analyst

Plano, TX · On-site

... our customers, our employees, and our company * Recommend actions based on your insights by ... High proficiency and professional experience with data acquisition, data manipulation, data ...

Recruit Monitor

Senior Data Analyst / Remote

Los Angeles, CA · Remote

$92K - $116K/yr

... and talent acquisition data (hiring, recruitment, etc.) to solve complex business problems. At ... Conduct training to business analysts and internal customers on data and resources available ...

Acquisition Professionals LLC

Data Analyst

New Orleans, LA · On-site

$55K - $65K/yr

Acquisition Professionals (AP) LLC is a trusted strategic partner and solutions-based company that ... The Data Analyst provides technical, analytical, and administrative support. This role supports the ...

next page

Showing results 1-20

All JobsBusiness JobsMarketing JobsConsumer Marketing Specialist JobsCustomer Acquisition Data Analyst Jobs

Customer Acquisition Data Analyst information

See salary details

$34K

$82.6K

$136K

How much do customer acquisition data analyst jobs pay per year?

As of Sep 12, 2026, the average yearly pay for customer acquisition data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What is the difference between Customer Acquisition Data Analyst vs Marketing Data Analyst?

AspectCustomer Acquisition Data AnalystMarketing Data Analyst
Required CredentialsBachelor's in Data Science, Marketing, or related field; proficiency in analytics toolsBachelor's in Marketing, Business, or related; strong analytical skills
Work EnvironmentData-driven teams focusing on customer acquisition strategiesMarketing departments analyzing campaign performance
Employer & Industry UsageTech, e-commerce, SaaS companies focusing on growthRetail, consumer goods, service industries

While both roles involve data analysis, the Customer Acquisition Data Analyst specializes in analyzing data to optimize customer acquisition efforts, whereas the Marketing Data Analyst covers broader marketing activities, including brand awareness and campaign analysis. The roles often overlap but differ in focus and specific metrics used.

What cities are hiring for Customer Acquisition Data Analyst jobs?

Cities with the most Customer Acquisition Data Analyst job openings:

What states have the most Customer Acquisition Data Analyst jobs?

States with the most job openings for Customer Acquisition Data Analyst jobs include:

What are popular job titles related to Customer Acquisition Data Analyst jobs?

For Customer Acquisition Data Analyst jobs, the most frequently searched job titles are:

Infographic showing various Customer Acquisition Data Analyst job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Senior Data Analyst, User Acquisition

Glendale, CA

Age of Learning, Inc.
E-Learning • 501 - 1,000 employees
Learn more about Age of Learning, Inc.external

$91K - $114K/yr

Full-time

Posted 22 days ago

Job description

Summary: 

We are seeking a proactive, intellectually curious Senior Data Analyst to support our User Acquisition team. 

Partnering closely with User Acquisition, Marketing, Data Engineering, and other analytics partners, you will analyze channel, campaign, audience, creative, and landing-page performance to identify opportunities that improve customer acquisition and marketing efficiency. 

You will evaluate both short-term conversion and long-term customer value and translate complex analyses into clear, actionable recommendations that guide acquisition strategy and investment decisions. To support this work, you will develop, maintain, and enhance Lifetime Value (LTV) models and apply a strong understanding of the broader acquisition measurement framework, including Customer Acquisition Cost (CAC), payback period, and Return on Advertising Spend (ROAS).

Responsibilities: 
  • Analyze acquisition performance: Evaluate results across channels, campaigns, audiences, creatives, devices, and landing pages to identify performance drivers, trends, and optimization opportunities. 
  • Apply acquisition measurement frameworks: Use Lifetime Value (LTV), Customer Acquisition Cost (CAC), payback period, and Return on Advertising Spend (ROAS) to assess customer value, compare acquisition efficiency, and guide investment allocation. 
  • Measure marketing effectiveness: Apply attribution, incrementality testing techniques, and support the development of Marketing Mix Modeling (MMM) capabilities. 
  • Define success metrics: Establish Key Performance Indicators (KPIs) for acquisition volume, efficiency, customer quality, and long-term value. 
  • Identify opportunities: Proactively detect performance changes, investigate root causes, and communicate risks and opportunities. 
  • Build reporting tools: Create self-service dashboards and automated reporting for business partners. 
  • Partner on data development: Work with User Acquisition and Data Engineering to define requirements and build scalable acquisition data models. 
  • Communicate insights: Present clear, actionable recommendations to technical and nontechnical stakeholders. 

Minimum Qualifications:
  • 6+ years of experience in user-acquisition, growth, marketing, or data analytics. 
  • Bachelor's or Master's degree in a quantitative field. 
  • Strong experience analyzing paid search, paid social, display, affiliate, mobile, connected television, or similar acquisition channels. 
  • Experience developing LTV, CAC, payback period, and ROAS models. 
  • Experience with attribution, incrementality testing, or related marketing-measurement methods. 
  • Advanced SQL skills and experience working with large datasets. 
  • Proficiency in Python or R for statistical analysis, modeling, automation, and visualization. 
  • Experience with Business Intelligence (BI) tools such as Omni, Looker, or Tableau. 
  • Experience with Snowflake, Git, or data build tool (dbt) is a plus. 
  • Ability to work independently, manage multiple priorities, and take projects from problem definition through recommendation. 
  • Strong written and verbal communication skills. 

Apply