Remote Algorithm Engineer Jobs in Downingtown, PA

At Forbes Advisor, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance so they can make informed decisions they feel confident in and get back to doing the things they care about most.
We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Forbes Advisor boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Forbes Advisor's global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.
Our Data & Analytics organisation builds the products, platforms and intelligence that power every marketing, product and commercial decision across the business. We're looking for a Data Science leader who believes machine learning only creates value when it changes business decisions.
This is an opportunity to build and lead a commercially driven Data Science function that delivers measurable improvements in customer acquisition, marketing performance and long-term business growth.
You'll lead a growing team of Data Scientists while partnering closely with Engineering, Analytics, Product and Commercial teams to ensure predictive models become trusted, production-ready products that drive measurable commercial outcomes. As we continue investing in first-party data, AI, machine learning and advanced marketing measurement, we're looking for an experienced Data Science leader to help shape the next phase of our commercial Data Science capability.
Responsibilties:

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

Qualifications:

• 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.

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