Data Scientist

About The Company

Our company is a renowned leader in the entertainment industry, celebrated for creating memorable experiences that unite audiences worldwide. We operate across multiple facets of entertainment, including live events, ticketing platforms, digital content, and subscription services, connecting millions of fans with their favorite content and moments.

Despite our extensive scale, we maintain a startup mentality characterized by agility, collaboration, and a relentless pursuit of innovation. We leverage cutting-edge technologies and advanced analytics to make smarter business decisions, enhance customer engagement, and deliver personalized experiences. Our commitment to fostering a dynamic, inclusive environment empowers our teams to take ownership, explore new ideas, and contribute meaningfully to shaping the future of entertainment.

About The Role

We are seeking a skilled professional specializing in Marketing Analytics, with a focus on customer acquisition cost (CAC), lifetime value (LTV), and subscription metrics. This role is integral to our data-driven decision-making processes, working at the intersection of data science, product development, and business strategy.

The successful candidate will develop predictive models to optimize marketing efforts, improve customer retention, and maximize revenue streams. This position offers the opportunity to work within a fast-paced, innovative environment that combines the scale and brand recognition of a major entertainment company with the agility of a startup. You will collaborate closely with cross-functional teams, including marketing, product, and analytics, to translate complex data insights into actionable strategies that enhance customer engagement and business growth.

Qualifications

The ideal candidate will have between 3 to 5 years of experience in data science, analytics, or related fields, with a proven track record of building models related to churn prediction, LTV, CAC, or similar consumer metrics.

• Proficiency in Python and SQL is essential.
• Experience working with modern data platforms such as Snowflake and cloud environments like AWS.
• A solid understanding of statistical methods, machine learning techniques, and experimental design.
• Experience handling large, complex datasets and deriving actionable insights.
• Ability to thrive in a dynamic, fast-paced environment.
• Excellent communication skills to convey technical findings to non-technical stakeholders.

Responsibilities

The core responsibilities of this role include:

1. Developing and maintaining predictive models for churn, LTV, and CAC to inform strategic growth and retention initiatives.
2. Analyzing ticket sales data to identify trends, forecast demand, and optimize pricing and promotional strategies.
3. Generating insights into customer behavior across subscription and transactional products to refine marketing efforts.
4. Collaborating with product, marketing, and analytics teams to translate business needs into effective data-driven solutions.
5. Designing and analyzing A/B tests to evaluate product features, campaigns, and pricing strategies.
6. Building scalable data pipelines and workflows in partnership with data engineering teams.
7. Communicating findings effectively to both technical and non-technical audiences to drive impactful decisions.

Benefits

Joining our team offers numerous benefits, including the opportunity to work with a leading brand in the entertainment sector.

• Culture that promotes innovation, ownership, and impact.
• Fully remote work setup.
• Competitive compensation packages.
• Comprehensive benefits, including health insurance, retirement plans, and professional development opportunities.
• Collaborative and inclusive workplace that values diversity.

Equal Opportunity

Our company is committed to creating an inclusive environment and is proud to be an Equal Opportunity Employer. We welcome and celebrate diversity in all forms and ensure that all qualified candidates receive fair consideration for employment regardless of race, color, sex, sexual orientation, gender identity, religion, national origin, age, disability, military status, genetic information, or any other protected characteristic under applicable laws.