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Forbes Advisor

Director of Data Science (Remote)

London
Posted 1 day ago
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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.
  • Shape the next phase of our commercial Data Science capability as we continue investing in first-party data, AI, machine learning, and advanced marketing measurement.

Responsibilties

Commercial Data Science

  • 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.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

Start with a chat, not a search bar

Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

Marketing Science & Decision Science

  • Partner with Marketing, Product, and Commercial teams to apply Data Science to real business problems.
  • 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.
  • 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.
  • 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.
  • 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.

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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.

Forbes Advisor provides equal employment opportunities

Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

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Skills

Data Science
Machine Learning
Predictive Analytics
Customer Analytics
Statistical Modelling
SQL
Python
Marketing Science
Decision Science
Model Monitoring
Stakeholder Management
Commercial Judgement
AI
Cloud Environments
Causal Inference
Experimentation

Location

London, England, United Kingdom

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