Data Scientist, AI Delivery

Salary: £53,000 - 86,000 per year

Requirements:

• Bachelors degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; a Masters degree or PhD in a relevant technical discipline is preferred.
• 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or in a similar role working with large-scale data and production environments; customer-facing or consulting experience is strongly preferred.
• Proficiency in Python, including Pandas, and core machine learning libraries such as TensorFlow, Keras, scikit-learn, CatBoost, and XGBoost.
• SQL skills for querying and manipulating datasets, with experience in machine learning pipelines and model deployment.
• Ability to write well-structured, modular, documented code and follow development practices such as Git, CI/CD, testing frameworks, type hinting, and code reviews.
• Ability to build scalable, maintainable solutions.
• Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into business value.
• Able to identify opportunities and risks early, troubleshoot obstacles, and develop creative solutions.
• Clear communication skills, including the ability to explain complex technical ideas to technical and non-technical audiences.
• Nice to have: experience with DevOps tools such as Airflow, Kubernetes, Terraform, or GCP; data integration, ETL, and pipeline optimization; or reinforcement learning algorithms.
• Curiosity about industry trends and new technologies, and the ability to thrive in an environment that encourages continuous learning and growth.

Responsibilities:

• Design machine learning use cases from the ground up, scoping solutions for business value, accounting for complex marketing journeys, and identifying risks early.
• Build and own full machine learning pipelines, from transforming customers raw data through model training and activation, to personalize experiences for millions of end users.
• Provide ongoing technical guidance to customers to support data science performance, successful adoption, and measurable outcomes.
• Develop features and tools that extend product capabilities and help scale AI deployments across engagements.
• Partner with the Braze Product team to refine and advance Brazes reinforcement learning algorithms and the platforms self-learning capabilities.
• Bring customer-facing insights and technical expertise to help shape the BrazeAI product strategy and roadmap.

Technologies:

• AI
• Airflow
• CI/CD
• DevOps
• ETL
• GCP
• Git
• Support
• Keras
• Kubernetes
• Machine Learning
• Marketing
• Model Training
• Python
• SQL
• TensorFlow
• Terraform
• pandas
• Cloud
• AI Agents

More:

We are Braze, a customer engagement platform that helps brands deliver valuable customer experiences. Our platform and BrazeAI support cross-channel messaging, journey orchestration, AI-powered decisioning, and personalized customer engagement. We are a collaborative, kind, and passionate team that values high standards, teamwork, work-life harmony, autonomy, accountability, and diverse perspectives. We offer benefits that may include competitive compensation and equity, retirement and employee stock purchase plans, flexible paid time off, medical, dental, vision, life and disability coverage, family services, professional development, employee resource groups, community giving opportunities, and a curated in-office experience; benefits vary by location. We are headquartered in New York, with offices in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, São Paulo, Singapore, Seoul, Sydney, and Tokyo. We are committed to an equitable, accessible, and inclusive candidate experience. Our recruitment process uses AI-assisted tools at certain stages for application review and administrative support, while our recruiting teams remain responsible for hiring decisions.

last updated 39 week of 2026