Applied AI Scientist
10 hours ago
London
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 with LLMs, prompt engineering, vector search or Agentic AI systems., • Experience using dbt or similar tools for feature layer creation., • Experience building real-time or near-real-time ML solutions., • Familiarity with data governance, model monitoring and responsible AI principles. Behavioural Skills • Curious, experimental and outcome-oriented, • Strong commercial awareness with an ability to connect your work to business value, • Comfortable working at speed while maintaining rigour, • Collaborative, proactive and eager to learn and teach others. The Benefits • Annual Leave: 25 days + bank holidays, • Ability to buy and sell holiday days as well as the ability to bank days (tenure dependant), • Flexible working options: we are operating a hybrid working model with 3 days a week from the office, • Pension: Hargreaves Lansdown up to 6% matched contribution, • Employee share scheme, • Generous family friendly cover, • Private healthcare - Bupa, • Income protection, • Critical illness cover, • Life insurance cover, • Dental cover, • Optical cover, • Yulife app for access to employee wellbeing and discounts, • Perks at Work, cashback/discount shopping site, • Employee referral scheme, • Salary sacrifice program which includes cycle to work scheme, electric car scheme and season ticket loans, • Volunteering program, • Company events i.e. Christmas party, all-company event and other social/hosted events during the year (we have an active social committee!), • Team socials