Applied Scientist

Description

The team builds machine learning capabilities that help the company make better decisions and deliver better experiences and outcomes.

You will tackle hard, real-world ML problems and build scalable models and intelligent systems for several areas of the business.

You will join data engineers, ML engineers, analysts, product managers and business stakeholders to design, build and roll out ML solutions at scale, and you can shape both the scientific direction of the team's work and the products that use it.

The company is an online fashion retailer serving customers worldwide.

Responsibilities

• Build, ship and run machine learning models and data-driven solutions in live production systems.
• Use machine learning and optimisation methods to tackle complicated business problems.
• Work with engineers to move models into production and create dependable, scalable ML systems.
• Plan and analyse experiments and evaluation frameworks that show how well models perform and what business impact they have.
• Research, test and prototype new methods drawn from industry and academia.
• Collaborate closely with product and business stakeholders to find where ML can add value.
• Shape the team's technical and scientific direction by sharing knowledge, reviewing code and working together.
• Help define best practice in ML, experimentation and applied research across the company.

Requirements

• You enjoy applying machine learning to large, real-world problems and turning research into production systems with measurable impact.
• The team is particularly interested in candidates with experience in some of the following areas:
• Building and deploying machine learning models in production.
• Applying statistics, analytics and machine learning to complex business problems.
• Experience in one or more of the following areas:
• Building and applying ML solutions to complex business problems.
• Building predictive models, intelligent systems or decision-support tools on large-scale data.
• Turning research, experiments and analytical findings into production-ready solutions.
• Designing and assessing models with suitable performance, business and customer impact measures.
• Working through the full ML lifecycle, from defining the problem and experimenting to deployment and monitoring.
• Using quantitative, statistical or optimisation techniques to support decisions and product development.
• You are proficient in Python and modern ML frameworks such as PyTorch, TensorFlow or similar.
• You have worked with large datasets and distributed data processing systems.
• You follow solid software engineering practices, including testing, version control and maintainable code.
• You can explain technical ideas to both technical and non-technical audiences.
• You are curious, pragmatic and willing to learn, experiment and share what you know.
• You have taken ML products from ideation to production.
• You have worked in fast-paced, product-driven environments.
• You are familiar with cloud-native ML platforms and MLOps practices.
• You have publications, open-source contributions or other evidence that you keep up with ML and AI developments.
• Additional information

Conditions

Let the Talent team know, at any stage of the process, if you need adjustments in whatever form suits you best.

Benefits

• Employee discount.
• Access to employee sample sales.
• 25 days of paid annual leave plus an extra celebration day for a special moment.
• Private medical care scheme.
• A Fixed Annual Payment paid each year on top of your salary.
• Opportunities for personalised learning and in-the-moment experiences to help you grow in your role.