Customer Data Scientist information
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$81.9K - $99.9K
4% of jobs
$99.9K - $117.8K
9% of jobs
$133.1K is the 25th percentile. Wages below this are outliers.
$117.8K - $135.8K
11% of jobs
$135.8K - $153.7K
7% of jobs
The median wage is $159.5K / yr.
$153.7K - $171.7K
50% of jobs
$171.7K - $189.6K
2% of jobs
$189.6K - $207.6K
1% of jobs
$207.6K - $225.5K
0% of jobs
$225.5K - $243.5K
13% of jobs
How much do customer data scientist jobs pay per year?
As of Aug 25, 2026, the average yearly pay for customer data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.
Customer Data Scientists are professionals who analyze customer data to identify patterns, trends, and insights that help businesses improve their products, services, and marketing strategies. They use statistical methods, machine learning, and data visualization tools to understand customer behaviors and preferences. By interpreting complex data sets, Customer Data Scientists enable companies to make data-driven decisions that enhance customer experience and drive business growth.
Customer Data Scientists often work closely with marketing and product teams to analyze customer behavior, segment audiences, and identify opportunities for personalized engagement. They translate complex data insights into actionable recommendations that guide campaign strategies and product improvements. Regular collaboration may include presenting findings, participating in cross-functional meetings, and building data models tailored to specific business objectives. This teamwork ensures that data-driven decisions directly support business growth and enhance the customer experience.
To thrive as a Customer Data Scientist, you need strong analytical skills, a solid background in statistics or mathematics, and proficiency in data modeling, usually supported by a degree in a quantitative field. Familiarity with tools like Python, R, SQL, and data visualization platforms such as Tableau or Power BI, along with experience using machine learning frameworks, is typically required. Strong communication, problem-solving abilities, and business acumen help translate complex data insights into actionable strategies for stakeholders. These skills are essential for driving data-driven decisions that enhance customer experiences and support business growth.
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