Job Specifications
About Reward
Founded in 2001, Reward is an industry leader transforming the world of customer engagement and commerce media. Operating in 15 countries across Europe, Middle East and Asia, Reward’s cloud-based API platform integrates content, advertising, and commerce to deliver exceptional experiences for consumers resulting in increased customer engagement, retention, and overall satisfaction.
Reward’s Loyalty-tech platform is behind many award-winning bank loyalty programmes seen today from brands such as Visa, NatWest Group, Barclays, and First Abu Dhabi Bank to name a few. Reward also works with the world’s largest retailers such as McDonald’s, eBay, Deliveroo and Amazon.
Their leading commerce media platform fuses purchase insights with loyalty-tech, offering an unparalleled edge in digital advertising and performance marketing for retailers. Leveraging rich data and insights, the Reward platform provides a comprehensive view of consumer behaviour, empowering retailers to target marketing messages more effectively, resulting in independently verified sales uplift and long-term customer lifetime value.
Beyond bridging the gap between content and commerce, Reward is a purpose driven business. Their mission is to make everyday spending more rewarding. During the last 5 years, Reward has proudly given back more than $1billion in cashback rewards to consumers world-wide.
Most recently, Reward’s rapid growth was recognised in The Independent’s E2ETech100 list of fastest growing tech scale-ups in the UK. Reward, in conjunction with partners NatWest Group, was also awarded the Industry Achievement Award 2023 at the prestigious Card and Payments Awards.
Role Summary
As an Applied AI Scientist, you will play a key role in developing, experimenting with and deploying advanced AI and machine learning products that deliver clear commercial value. Reporting to the Analytics Engineering Manager, you will work across the full ML lifecycle; from exploratory research and rapid prototyping to production deployment and ongoing optimisation.
You will combine strong experimentation skills with hands-on engineering capability, delivering practical AI solutions such as forecasting engines, personalisation models, segmentation, attribution and advanced revenue optimisation. You will also innovate with emerging technologies including LLMs, Agentic AI and automation frameworks, shaping how AI is adopted across the organisation.
You will collaborate closely with Data Engineers, Analytics Engineers and business stakeholders, while also mentoring junior analysts and fostering a culture of data science excellence.
Responsibilities
AI & ML Product Development
Research, design and prototype advanced ML models, including forecasting, segmentation, attribution and uplift modelling
Develop personalised recommendation and propensity models that drive commercial uplift
Lead experimentation and PoC development in areas such as Agentic AI, GenAI workflows and LLM-based automation
Translate business problems into ML/AI solutions that deliver measurable outcomes.
End-to-End AI Delivery
Own the full AI lifecycle: data sourcing, feature engineering, model building, evaluation, deployment and monitoring
Build production-ready ML pipelines using AWS technologies including SageMaker, Bedrock, Redshift and S3
Collaborate with Data Engineers to operationalise models and integrate ML solutions into production systems
Establish best practices for model reproducibility, testing, monitoring and AIOps workflows.
Collaboration & Stakeholder Engagement
Work cross-functionally with Analytics Engineering, Product, Marketing and Commercial teams to translate needs into model-led solutions
Communicate complex technical concepts in ways that influence non-technical stakeholders
Partner with product teams to embed AI models into customer experiences and internal applications.
Coaching & Thought Leadership
Mentor junior Analysts, helping uplift skills in modelling, Python, experimentation and statistical thinking
Introduce new techniques, tools and frameworks to accelerate AI capability across the data organisation
Support the creation of internal standards, documentation and governance for AI/ML products.
Requirements
Minimum Qualifications
Experience in applied machine learning, AI or data science, with hands-on delivery of production AI models
Proficiency in Python, SQL and modern ML frameworks
Experience with AWS AI/ML tools, including SageMaker, Bedrock, Redshift and S3 or similar tools
Ability to build end-to-end ML solutions including data prep, feature engineering, model training, deployment and monitoring
Strong understanding of forecasting, segmentation, personalisation, uplift modelling and attribution methodologies
Experience with ML/AIOps practices, CI/CD, model versioning and automation workflows
Ability to prototype rapidly while maintaining engineering discipline and code quality.
Preferred Qualifications
Hands-on experience
About the Company
Founded in 2001, Reward is an industry leader transforming the world of Customer Engagement and Commerce Media.
Operating in 15 countries across Europe, Middle East and Asia, Reward’s cloud-based API platform integrates content, advertising, and commerce to deliver exceptional experiences for consumers resulting in increased customer engagement, retention, and overall satisfaction.
Reward’s technology platform is behind many award-winning bank loyalty programmes seen today from brands such as Visa, NatWest Group, Barclay...
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