Manager, Lifecycle Marketing Analytics

New

PrizePicksDaily fantasy sports

We are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidatesFull-TimeManager

SalaryThe typical salary range for this position is $190,000 to $210,000.

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Job Details

Experience: 5+ years of experience in lifecycle, CRM, retention, or growth analytics; 1+ year of experience managing analysts
Required Skills: PythonSQLTableauMicrosoft ExcelA/B testingdbt

Have 5+ years of experience in lifecycle, CRM, retention, or growth analytics.
Have 1+ year of experience managing analysts.
Have proven experience measuring and optimizing promotional, incentive, or reinvestment spend.
Have deep experimentation experience, including A/B testing, holdout design, and power analysis.
Have experience supporting targeted and triggered lifecycle programs at scale.
Have experience partnering with CRM teams and platforms; Braze is strongly preferred.
Have hands-on experience applying AI tools, such as LLMs or coding assistants, to analytics workflows and coaching others to adopt them.
Have advanced SQL and Excel skills.
Have experience with Tableau or a similar BI tool; Tableau is strongly preferred.
Python for statistical analysis, experimentation, or automation is preferred.
Experience with dbt or similar data transformation tools is preferred.
Experience with cross-product adoption or cross-sell strategy is preferred.
Experience in daily fantasy, gaming, or another app-based B2C business is preferred.

Lead a team of data analysts covering lifecycle, promotions, and CRM.
Deliver data-driven insights and recommendations to senior leadership.
Measure promotional and reinvestment spend, including incrementality, ROI, and offer optimization.
Set experimentation standards, including hypothesis development, test design, power analysis, and holdout strategy.
Measure and optimize onboarding, first-time deposit conversion, retention, and reactivation programs.
Develop targeting, pricing, and measurement strategies for cross-product adoption and cross-sell campaigns.
Partner with the CRM team to define audience, eligibility, and trigger logic for campaigns executed in Braze.
Build scalable analytics solutions such as automated test readouts, always-on holdouts, and audience pipelines.
Drive adoption of AI tools, including LLMs, in analytics and lifecycle workflows.

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