Lead Data Scientist

Versant•Universal City, CA

13d•Hybrid

About The Position

VERSANT is seeking a Lead Data Scientist to serve as the senior technical leader for the Fandango and Rotten Tomatoes analytics organization. This senior individual-contributor role has organization-wide influence and no direct reports, and reports to the head of the Fandango and Rotten Tomatoes Analytics organization. The role builds models, frameworks, and processes that advance the delivery of data products to the business. The Lead Data Scientist owns core modeling work—including customer segmentation, lifetime value, retention, and forecasting—and establishes methodological standards for experimentation and causal inference. The role also provides technical leadership in applying AI to analytical workflows, building and shipping solutions that improve speed and quality while addressing risk and bias. The successful candidate will create reusable models and standards, mentor colleagues, and help shift stakeholder delivery from one-off analyses toward durable, scalable, self-service data products. The role partners across Product, Engineering, Marketing, and Finance and communicates modeling results as actionable recommendations for senior leaders.

Requirements

A degree in a quantitative or technical field, or equivalent practical experience.
At least 7 years of experience in data science or analytics.
Experience leading technical work as an individual contributor and guiding data-informed strategy.
Hands-on expertise in predictive modeling and machine learning.
Experience building segmentation, customer lifetime value, and forecasting models.
Strong command of experimentation and causal inference, including experience setting organizational standards.
Expert SQL skills and proficiency with a modern data science toolkit.
Solid understanding of data pipelines and data modeling.
Technical leadership experience, including AI technical leadership.
Experience integrating AI tools to redesign workflows and drive measurable impact.
Proven ability to work across Product, Engineering, Marketing, and Finance.
Exceptional problem-framing and communication skills, including translating complex modeling into actionable recommendations for senior leaders.
A track record of mentoring and improving the technical capability of analysts or scientists.

Nice To Haves

Experience in media, streaming, entertainment, or consumer subscription and transactional businesses.
An advanced degree in a quantitative field.

Responsibilities

Lead core modeling work in customer segmentation, customer lifetime value, retention, and forecasting.
Set methodological standards for experimentation and causal inference.
Build models, frameworks, and processes that improve how data products are delivered to the business.
Develop segmentation models that help Product, Marketing, and Content target, personalize, and prioritize.
Build customer lifetime value models to inform acquisition spending, retention investment, and content decisions.
Develop retention models that provide a forward-looking view of customer retention and churn.
Deliver forecasts with clear assumptions, drivers, and accuracy.
Mentor team members and raise the technical rigor and speed of the analytics team's work through reusable models and standards.
Move stakeholder delivery toward durable, scalable, self-service data products that stakeholders trust and adopt.
Identify opportunities for AI to redesign analytical workflows, build solutions, and deliver measurable gains in speed and quality.
Promote responsible AI practices, including risk assessment and bias mitigation.
Work across Product, Engineering, Marketing, and Finance, translating complex modeling into recommendations senior leaders can act on.