Job Description
Marketing Analytics - CAC, LTV, Subscriptions
This Jobot Job is hosted by: Dylan Currier
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Salary: $100,000 - $130,000 per year
A bit about us:
We are a household name in the entertainment industry, known for delivering unforgettable experiences that bring people together. From live events and ticketing to digital and subscription-based offerings, we connect millions of fans with the content and moments they care about most.
Behind the scenes, we operate with the mindset of a startup—fast-moving, collaborative, and deeply focused on innovation. We’re constantly exploring new ways to better understand our customers, optimize their journey, and create more meaningful engagement through data.
Our teams leverage modern technologies and advanced analytics to power smarter decisions across the business. By combining creativity with data science, we’re able to enhance everything from ticket sales strategies to personalized subscription experiences.
We believe in empowering our people to take ownership, experiment, and make an impact. Whether it’s launching new products, refining customer insights, or building scalable data solutions, every team member plays a key role in shaping the future of entertainment.
Join us and help redefine how audiences discover, engage with, and experience live and digital entertainment.
Why join us?
Opportunity to work with a leading brand in the entertainment space
A dynamic, startup-oriented culture with room to make a direct impact
Fully remote work environment with flexibility
Competitive compensation and benefits
Job Details
We are looking for a Data Scientist to join a well-known, household-name company in the entertainment industry. This role sits at the intersection of data, product, and business strategy, with a strong focus on consumer analytics across ticketing and subscription-based offerings.
You will build and deploy models that drive key business metrics such as churn, lifetime value (LTV), and customer acquisition cost (CAC), while uncovering actionable insights to optimize ticket sales and customer engagement. This is an opportunity to work within a fast-moving, startup-like environment backed by the scale and brand recognition of a major entertainment company.
Key Responsibilities
Develop and maintain predictive models for churn, LTV, and CAC to inform growth and retention strategies
Analyze ticket sales data to identify trends, forecast demand, and optimize pricing and promotions
Generate insights on customer behavior across subscription and transactional products
Partner with product, marketing, and analytics teams to translate business needs into data-driven solutions
Design and analyze A/B tests to evaluate product features, campaigns, and pricing strategies
Build scalable data pipelines and workflows in collaboration with data engineering teams
Communicate findings clearly to both technical and non-technical stakeholders
Required Qualifications
3–5 years of experience in data science, analytics, or a related field
Proven experience building models related to churn prediction, LTV, CAC, or similar consumer metrics
Strong proficiency in Python and SQL
Experience working with modern data platforms such as Snowflake and cloud environments like AWS
Solid understanding of statistical methods, machine learning techniques, and experimental design
Experience working with large, complex datasets and deriving actionable insights
Ability to thrive in a fast-paced, startup-like environment
Preferred Qualifications
Experience in entertainment, media, ticketing, or subscription-based businesses
Familiarity with forecasting models and time-series analysis
Experience with data visualization tools (e.g., Tableau, Looker)
Exposure to big data tools (e.g., Spark)
Interested in hearing more? Easy Apply now by clicking the "Apply" button.
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