Director of Data Science

Forbes Advisor

Director of Data Science at Forbes Advisor leading predictive modeling and enhancing customer acquisition and marketing performance. Partnering with teams to execute AI-driven marketing strategies.

Posted 7/8/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

CloudPythonSQL

About the role

Key responsibilities & impact

Lead the strategy and delivery of predictive models that improve customer acquisition, marketing performance and long-term commercial value
Shape capabilities including lifetime value modelling, propensity modelling, customer segmentation, forecasting and value-based bidding, ensuring every model is linked to measurable business outcomes
Partner with Marketing, Product and Commercial teams to apply Data Science to real business problems
Define how predictive analytics, experimentation and AI improve campaign performance, customer understanding and strategic decision making across platforms including Google and Meta
Ensure models become reliable, production-ready products rather than one-off analyses
Champion reproducible experimentation, scalable deployment, model monitoring, retraining strategies and continuous improvement throughout the model lifecycle
Lead and develop a growing team of Data Scientists while building trusted relationships across the business
Translate complex modelling into clear commercial recommendations, influence senior stakeholders through evidence, and establish Data Science as a trusted driver of business strategy and commercial growth
Represent Forbes in strategic conversations with technology partners including Google and Meta while staying connected to advances in AI, machine learning and marketing science
Evaluate emerging technologies, bring new ideas into the organisation and help ensure Data Science capability remains commercially relevant and technically leading

Requirements

What you’ll need

Experience leading commercial Data Science, Marketing Science or Decision Science teams
Strong expertise in predictive analytics, customer analytics, machine learning and statistical modelling
Experience applying Data Science to marketing performance, customer acquisition, lifetime value or value-based bidding
Experience productionising machine learning solutions within modern cloud environments and working closely with Engineering and ML Ops teams
Strong understanding of SQL, Python and modern machine learning frameworks
Experience working with Google Ads, Meta or other major advertising platforms
Excellent stakeholder management and communication skills, with the ability to influence both technical and commercial audiences
Experience building and developing high-performing Data Science teams
Strong commercial judgement, balancing technical excellence with measurable business impact
A pragmatic approach to AI, applying emerging technologies where they create genuine commercial value.
Nice to Have: Experience within affiliate marketing, digital publishing or lead-generation businesses
Experience working in financial services, insurance or regulated industries
Experience working directly with Google or Meta Data Science teams
Experience with attribution modelling and marketing measurement
Experience building optimisation algorithms for DSPs or advertising platforms
Experience with causal inference, experimentation frameworks or incrementality testing
Experience forecasting marketing or commercial performance
Experience with Vertex AI or equivalent cloud-based machine learning platforms.

Benefits

Comp & perks

Equal employment opportunities to all employees and applicants for employment
Prohibits discrimination and harassment of any type

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Predictive ModellingCustomer SegmentationStatistical ModellingValue-Based BiddingAttribution ModellingCausal InferenceExperimentation FrameworksForecastingOptimisation AlgorithmsLifetime Value Modelling

Soft Skills

Stakeholder ManagementCommunication SkillsInfluencing SkillsCommercial JudgementPragmatic Approach