Lead Data Scientist
Awardco - Lindon, Utah
Posted Jan 5, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Lead Data Scientist Lindon, Utah Awardco is reimagining the workplace to be more rewarding, supportive, and fun for everyone. As one of the fastest-growing companies in the employee experience industry, our mission is to help employees love what they do, love where they work, and get recognized for their efforts-especially our own employees! And as winners of Glassdoor's Best Places to Work, Best in Brightest in the Nation, and Great Place to Work, we do much more than talk the talk. Summary Awardco is looking for a results-driven, hands-on leader to build and lead the Data Science function. The Data Operations group is responsible for delivering business insights and high-impact analyses to the various business units within Awardco. Within this group, the Lead Data Scientist will address strategic and operational questions facing our global business, including customer behavior, performance measurement, and product and marketing efficiency. This individual will partner with different business units to meet their analytic needs and conduct extensive analyses of Awardco's data, generate insights, and communicate those insights to the business. The Lead Data Scientist role is data and analytically intensive. Successful candidates will offer deep analytical capabilities and will be adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. What You Will Do Responsibilities - This position will enable data-driven business decisions by performing business and data analyses using a variety of techniques, ranging from simple data aggregation to
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