About Fresha

Fresha is the leading marketplace platform for beauty & wellness trusted by millions of consumers and businesses worldwide.

Fresha is used by 120,000+ businesses and 450,000+ stylists and professionals worldwide , processing over 1 billion appointments to date.

The company is headquartered in London, United Kingdom , with 12 global offices located across North America, EMEA and APAC.

Fresha allows consumers to discover, book and pay for beauty and wellness appointments with local businesses via its marketplace, while beauty and wellness businesses and professionals use an all-in-one platform to manage their entire operations with an intuitive subscription-free business software and financial technology solutions.

Fresha’s ecosystem gives merchants everything they need to run their business seamlessly by facilitating appointment bookings, point-of-sale, customer records management, marketing automation, loyalty, beauty products inventory and team management.

The consumer marketplace unlocks revenue potential for partner businesses by leveraging the power of online bookings and automated marketing through mobile apps and advanced integrations with major tech brands including Instagram , Facebook and Google.

Role overview

Given our exciting growth plans, we are looking for an exceptional Senior Data Scientist to join our growing Machine Learning team. You’ll lead the design and development of intelligent systems that power core product experiences – such as personalised recommendation engines, fraud detection pipelines, and AI-driven image moderation tools – all operating in real-time at global scale.

This is a hands-on, high-impact role. Reporting into the Head of Product (Product, Data Science, Analytics), you’ll collaborate closely with fellow data scientists, engineers, product managers, and designers to deliver models that serve millions of users – and meaningfully improve business outcomes.

This is a great opportunity for someone looking to work in a fast-paced and changing environment, who likes to work autonomously, enjoys a challenge and wants to make an impact.

To foster a collaborative environment that thrives on face-to-face interactions and teamwork, this role will be based in our dog-friendly office 4 days per week, with the flexibility to work remotely one day each week. London office address: The Bower, The Tower, 207 Old St, London EC1V 9NR

Accountabilities

• Design and implement advanced machine learning models for core product features – from ranking and recommendations to anomaly detection and image classification, and more
• Build real-time pipelines for serving ML models at scale (think: event-driven systems, stream processing, low-latency inference)
• Own the end-to-end lifecycle: from prototyping and experimentation to deployment and monitoring in production
• Collaborate with cross-functional teams to scope business needs and translate them into technical solutions
• Lead A/B testing efforts to measure the impact of ML models in production
• Mentor and coach an existing team of junior data scientists
• Stay on top of the latest in deep learning, LLMs, and applied research – and help bring cutting-edge ideas into production

Key skills

• Proven experience as a Machine Learning Scientist, with a strong track record of delivering robust, scalable models to solve real-world business problems in production environments.
• Deep understanding of core machine learning principles, with hands-on experience using modern frameworks such as PyTorch, TensorFlow, and Transformers to develop and deploy advanced models.
• Proficiency in Python, with the ability to write clean, production-grade code, and a solid understanding of data engineering workflows and MLOps best practices.
• Strong collaborator with excellent communication skills, capable of working effectively across cross-functional teams, including engineering, product, and design.
• Committed to continuous learning and staying current with advancements in machine learning research, tools, and best practices.
• Ambitious, determined, and self-motivated, able to navigate the fast-paced and dynamic environment at Fresha. Your ability to stay motivated, navigate challenges, and drive forward our data science offering will be crucial for your success.

Preferred experience

• Experience with MLOps tools and workflows, such as MLflow, Docker, KServe, and Feature Stores
• Familiarity with cloud-based environments, including containerisation on AWS and the use of cloud notebooks (e.g. SageMaker, Vertex AI, Hex)
• Exposure to modern data tooling such as DBT, Airflow, and distributed computing frameworks like Spark or Ray
• Experience building internal tools or dashboards using Streamlit or similar frameworks
• Experience in fast-paced, high-growth environments, ideally within product-led tech companies
• Comfort working on real-time systems or event-driven architectures (e.g. Kafka, Kinesis)

Inclusive workforce

At Fresha, we are creating a culture where individuals of all backgrounds feel comfortable.

We want all Fresha people to feel included and truly empowered to contribute fully to our vision and goals. Everyone who applies will receive fair consideration for employment.

If you have any accessibility requirements that would make you more comfortable during the interview process and/or once you join, please let us know so that we can support you.