Senior Data Scientist AI/ML

Werken als Senior Data Scientist AI/ML binnen het Core Platform-team

Purpose of the Role

Data sits at the heart of the company. This role ensures that Awin can fully leverage the data available across the group, enabling the development of robust reporting capabilities that support stronger commercial decision-making and elevate campaign management for client-facing teams.

As a Senior Data Scientist within the Core Platform team, you will drive the development, governance, and enablement of Awin’s AI platform. Your role focuses on defining best practice standards, shaping platform capabilities, and empowering product and engineering teams to build scalable, responsible AI solutions. You will guide the process and ensure that AI is adopted across the business, ensuring reliability, quality, and consistency, while also be expect to undertake MVP’s with product teams.

In this role, you will define AI and ML standards, reference patterns, and reusable components while partnering with engineering teams to evolve the AI platform for scalability, governance, and reliability. You will guide teams on AI solution design, data readiness, evaluation methods, and responsible AI practices, including generative AI approaches such as LLM orchestration and retrieval-augmented generation. You will assess emerging technologies, strengthen experiment and feature governance, and mentor teams to ensure consistent, high-quality AI adoption across the organisation.

Key Responsibilities

• Define, maintain and drive adoption of AI/ML standards, patterns, and reusable components to enable efficient model development across teams.
• Partner with Data Engineering and Platform Engineering to evolve core AI platform capabilities, ensuring scalability, governance, and robustness.
• Advise product teams on model design choices, data readiness, evaluation strategies, and responsible AI practices.
• Develop and implement frameworks, guidelines, and reference architectures to support enterprise-wide adoption of AI and generative AI.
• Evaluate new AI technologies, tools, and workflows, driving continuous improvement of the platform.
• Develop and maintain an AI experimentation sandbox that enables teams to prototype and test new models and tooling efficiently.
• Ensure data quality, feature standardization, and reproducibility across the AI lifecycle.
• Mentor and coach teams on AI methods, experimentation, and best-practice platform usage.
• Communicate complex concepts clearly to stakeholders, enabling strategic decision-making and alignment.

Education & Experience

• Bachelor’s degree or higher in Statistics, Mathematics, Data Science, AI/ML, or related field.
• 6+ years of experience in Data Science or AI, with strong exposure to platform-level enablement or ML Ops-aligned environments.
• Demonstrated expertise in generative AI models and tooling (e.g. standardized evaluation, AI-specific observability, safe rollback mechanisms, retrieval-quality assessment etc).
• Experience designing scalable AI architecture components, model pipelines, inference patterns, vector search, feature engineering standards, and monitoring frameworks.
• Proven experience of creating and maintaining end to end AI tools.
• Proven ability to mentor teams on AI methodologies, experimentation, and adoption of platform tooling.
• Collaborative, proactive, and customer-focused approach to enabling product and engineering teams.

Skills & Core Competencies

• Strong collaboration skills when working with Data Engineers, ML Engineers, and Software Engineers on platform-level solutions.
• Deep understanding of AI/ML lifecycle needs, feature stores, experiment tracking, model evaluation, governance, and reproducibility.
• Expertise in modern AI and generative AI frameworks, including LLM orchestration, retrieval-augmented generation (RAG), agentic workflows, and prompt engineering best practices.
• Strong ability to assess AI use-cases, guide teams on model selection and design patterns (traditional ML vs. LLM vs. hybrid approaches), and ensure responsible, secure AI usage.
• Experience designing scalable AI architecture components, model pipelines, inference patterns, vector search, feature engineering standards, and monitoring frameworks.
• Ensure thoughtful cost stewardship across AI systems by treating efficiency, resource usage, and value-for-impact as core engineering considerations.
• Ability to translate business and product requirements into platform-level capabilities, reusable components, and best-practice guidelines.

Our Offer

• Flexi-Week and Work-Life Balance: We prioritise your mental health and wellbeing, offering you a flexible four-day Flexi-Week at full pay and with no reduction to your annual holiday allowance. We also offer a variety of different paid special leaves.
• Remote Working Allowance: You will receive a monthly allowance to cover part of your running costs. In addition, we will support you in setting up your remote workspace appropriately.
• Flexi-Office: We offer an international culture and flexibility through our Flexi-Office and hybrid/remote work possibilities to work across Awin regions.
• Meal Vouchers: You will be supported with a certain net sum to spend it on a variety of lunches.
• Health & Wellbeing: The insurance covers several types of health, vision and / or dental treatments for you and for up to one additional family member.
• Remote Working Furniture Package: After 3 months of employment, you will be eligible for a furniture package, which should enable you to set up a proper workplace at your remote working location.
• Appreciation: Thank and reward colleagues by sending them a voucher through our peer-to-peer program.

Established in 2000, Awin is proud of our dynamic, social and inclusive culture.

Like all businesses, we’ve had to adapt and nurture our culture in a virtual environment. Our virtual ‘Life @ Awin’ hub brings our colleagues from across the globe together for various social activities.