Lead Data Scientist

VERSANT (Nasdaq: VSNT) is an industry-changing media and entertainment business and home to trusted brands that shape culture, inform audiences, and build lasting connections. It operates across four core markets: political news and opinion, business news and personal finance, golf, and sports and genre entertainment. These markets are served through a powerful portfolio of iconic and innovative brands, including CNBC, MS NOW, USA Network, Golf Channel, Oxygen, E!, SYFY, and Versant's sports division USA Sports, along with complementary digital assets including Fandango, Rotten Tomatoes, GolfNow and GolfPass.

About the role

We're looking for a Lead Data Scientist to be the senior technical leader for our Fandango and Rotten Tomatoes analytics organization. You'll build the models, frameworks, and processes that transform how we deliver data products to the business. You'll own our core modeling work: segmentation, customer lifetime value, retention, and forecasting. You will set the methodological standard for how we run experiments. You'll also bring modern AI technical leadership to how we build and ship analytics. This is a senior individual contributor role with organization-wide influence and no direct reports, reporting to the head of the Fandango and Rotten Tomatoes Analytics.

Responsibilities

• The business can act on who its customers are. Your segmentation work becomes how Product, Marketing, and Content target, personalize, and prioritize.
• We invest against long-run value. Your customer lifetime value models let the business weigh acquisition spend, retention investment, and content decisions against what a customer is actually worth.
• We can predict who stays and who leaves. Your retention modeling gives the organization a forward-looking view instead of a rear-view mirror.
• The business can plan with confidence. Your forecasts come with clear assumptions, drivers, and accuracy.
• Our experiments are statistically sound. You own the methodology and causal-inference standards, so the conclusions we draw hold up.
• Every team member gets better. The frameworks, reusable models, and standards you build raise the rigor and speed of the entire team's work through your mentorship.
• We ship data products, not one-off analyses. You change how we deliver to stakeholders, moving toward durable, scalable, self-service products people trust and adopt.
• AI meaningfully changes how we work. You identify where AI can redesign analytical workflows, build those solutions, and deliver measurable gains in speed and quality.
• We do this responsibly. You champion sound AI practices, risk assessment, and bias mitigation.

Qualifications

• A degree in a quantitative or technical field, or equivalent practical experience.
• 7+ years in data science or analytics, including leading technical work as an individual contributor and guiding data-informed strategy.
• Hands-on expertise in predictive modeling and machine learning, with experience building segmentation, lifetime-value, and forecasting models.
• Strong command of experimentation and causal inference, and experience setting those standards for an organization.
• Expert SQL and a modern data science toolkit, with a solid grasp of pipelines and data modeling.
• Technical leadership experience, including AI technical leadership. You've integrated AI tools to redesign workflows and drive measurable impact.
• Proven success working across Product, Engineering, Marketing, and Finance.
• Exceptional problem framing and communication. You turn complex modeling into recommendations senior leaders act on.
• A track record of mentoring and raising the technical capability of other analysts or scientists.
• Preferred Experience in media, streaming, entertainment, or consumer subscription and transactional businesses.
• An advanced degree in a quantitative field.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• 401(k)
• Paid leave
• Tuition reimbursement
• Various discounts and perks

Pay

$170,000 - $190,000 (bonus eligible)

Schedule

Hybrid: This position has been designated as hybrid, generally contributing from the office a minimum of three days per week. Subject to change based on business need.