Data Scientist (Customer Focus)

Role overview

Our client is a global organisation seeking a practical Data Scientist who is motivated by solving real-world operational challenges with data. Rather than working on models in isolation, this role focuses on using live industrial, sensor, and time-series datasets to identify failure trends, enhance equipment performance, and support better decision-making for customers.

The position sits within a fast-moving, collaborative environment where data science is applied directly to live business and operational settings. You will contribute to a modern industrial IoT and AI platform that combines cloud streaming, operational analytics, and new AI/LLM capabilities. The business has a strong commitment to innovation and a track record of developing people internally, creating room for long-term growth alongside the technology.

A significant part of the role is customer-facing. You will engage with both technical and non-technical stakeholders, so the ability to explain complex concepts clearly and practically is essential. Some international travel will be required from time to time.

Key responsibilities

• Analyse high-volume industrial and sensor datasets to identify meaningful trends and opportunities.
• Create predictive analytics solutions and reporting tools using Python.
• Detect patterns, anomalies, and early warning signs of equipment issues or failure.
• Translate complex findings into straightforward recommendations that customers can put into action.
• Deliver demonstrations, workshops, and customer-facing presentations.
• Work in close partnership with commercial teams, engineers, and customers to design effective solutions.
• Help implement and improve analytics tools used in live operational settings.
• Support the development of a new-generation industrial IoT and AI platform.

Required profile

• Previous experience in a Data Scientist position.
• Strong Python capability, including hands-on use of pandas, numpy, and scikit-learn.
• Experience working with time-series, IoT, sensor, manufacturing, or other operational data.
• Commercial awareness and an understanding of how analytics delivers customer value.
• Confidence in presenting ideas and insights to varied audiences.
• Background in customer-facing, consulting, or highly collaborative environments.
• Exposure to cloud environments such as Azure or to production-based settings.
• A degree in a technical discipline such as Data Science, Engineering, Maths, or Physics.

Package and benefits

• Competitive base salary.
• Private medical cover.
• Discretionary bonus.
• 8% employer pension contribution.
• Life insurance.
• Enhanced maternity and paternity leave package.
• Recognition and reward scheme.

Additional information

The employer is committed to diversity and inclusion and aims to provide equal opportunity for all candidates. Reasonable adjustments can be discussed if needed.