Kajabi · 3 hours ago

Principal Data Scientist, Analytics

United States

Full-time

Remote

Lead/Staff

$143K/yr - $191K/yr

8+ years exp

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CRME-Commerce

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Responsibilities

Develop a deep understanding of Kajabi’s data landscape to identify opportunities for analytics-driven improvements.

Deliver actionable recommendations to stakeholders across multiple teams to support company-wide objectives.

Partner closely with Product, Marketing, Finance, Engineering, and Operations to define and track metrics that directly impact Kajabi’s OKRs related to user growth, engagement, and revenue.

Leverage advanced statistical and machine learning techniques to build models for forecasting, ROI analysis, performance marketing, customer lifetime value (LTV), and recommendation systems.

Optimize these models to ensure their relevance and accuracy in driving business outcomes.

Analyze and communicate how key initiatives influence Kajabi’s top-line and bottom-line metrics, providing data-backed recommendations that support company growth.

Act as a thought leader by presenting data-driven insights and recommendations to senior leadership, influencing strategic decisions to maximize growth and engagement.

Continuously monitor and refine analytics processes to improve data accuracy, scalability, and accessibility across the organization.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data ScienceSQLPythonRMachine LearningPerformance MarketingROI AnalysisCustomer Lifetime Value (LTV)ForecastingRecommendation SystemsCross-Functional Collaboration

Required

8+ years of experience in data science, analytics, or a related field, with a successful track record of driving top-line and bottom-line impact, preferably within a SaaS or tech environment.

Proficient in advanced data analysis tools and programming languages such as SQL, Python, and R, and experienced in developing and operationalizing machine learning models.

Demonstrated ability to translate complex data insights into strategic recommendations, especially in areas like performance marketing, ROI, LTV, forecasting, and recommendation systems.

Proven experience collaborating effectively across Product, Marketing, Engineering, Finance, and Operations, with the ability to influence senior leadership.

Strong analytical and problem-solving skills, with a proactive approach to identifying opportunities for data-driven improvements.

Excellent written and verbal communication skills, with the ability to clearly articulate technical concepts to non-technical audiences.