Director of Data Science

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead the strategy and implementation of predictive models that enhance customer acquisition, marketing effectiveness, and long-term commercial value.

• Develop capabilities such as lifetime value modeling, propensity modeling, customer segmentation, forecasting, and value-based bidding, ensuring that every model is tied to measurable business results.

• Collaborate with Marketing, Product, and Commercial teams to leverage Data Science in addressing real business challenges.

• Define the ways in which predictive analytics, experimentation, and AI can enhance campaign performance, customer insights, and strategic decision-making across platforms like Google and Meta.

• Ensure models transition into reliable, production-ready products rather than standalone analyses.

• Advocate for reproducible experimentation, scalable deployment, model monitoring, retraining strategies, and ongoing enhancement throughout the model lifecycle.

• Lead and nurture a growing team of Data Scientists while fostering trusted relationships across the organization.

• Simplify complex modeling into clear commercial insights, influencing senior stakeholders through evidence and establishing Data Science as a key driver of business strategy and growth.

• Represent Forbes in strategic discussions with technology partners such as Google and Meta, while staying informed about advancements in AI, machine learning, and marketing science.

• Assess emerging technologies, introduce innovative ideas into the organization, and ensure that Data Science capabilities remain commercially relevant and technically advanced.

⛳️ Requirements

• Proven experience in leading commercial Data Science, Marketing Science, or Decision Science teams.

• Strong expertise in predictive analytics, customer analytics, machine learning, and statistical modeling.

• Experience in applying Data Science to enhance marketing performance, customer acquisition, lifetime value, or value-based bidding.

• Experience in deploying machine learning solutions within modern cloud environments, in close collaboration with Engineering and ML Ops teams.

• Strong proficiency in SQL, Python, and contemporary machine learning frameworks.

• Familiarity with Google Ads, Meta, or other prominent advertising platforms.

• Excellent stakeholder management and communication abilities, with the capacity to influence both technical and commercial stakeholders.

• Proven experience in building and developing high-performing Data Science teams.

• Strong commercial insight, balancing technical excellence with measurable business impact.

• A pragmatic approach to AI, utilizing emerging technologies where they deliver genuine commercial value.

• Nice to Have: Experience in affiliate marketing, digital publishing, or lead-generation sectors.

• Background in financial services, insurance, or regulated industries.

• Direct experience working with Google or Meta Data Science teams.

• Familiarity with attribution modeling and marketing measurement.

• Experience in creating optimization algorithms for DSPs or advertising platforms.

• Knowledge of causal inference, experimentation frameworks, or incrementality testing.

• Experience in forecasting marketing or commercial performance.

• Familiarity with Vertex AI or similar cloud-based machine learning platforms.

🏝️ Benefits

• Equal employment opportunities for all employees and job applicants.

• Prohibition of discrimination and harassment of any kind.