Data Scientist - Customer Focus

As a Data Scientist - Customer Focus, your mission is to turn complex data into practical insights and predictive solutions that help improve equipment performance, reduce downtime, and support better operational decision-making. In this role, you will work closely with customers, account teams, and technical specialists, giving you the chance to see the direct impact of your work in real operational environments while building experience at the intersection of technology, customer collaboration and business value.

This is an exciting opportunity to work at the forefront of data science and industrial innovation, applying advanced analytics to solve real customer challenges on a global scale.

You will

• Explore, prepare, and deliver data analyses, predictive models, and reporting that create measurable value for global customers.
• Work closely with customers and account teams to rapidly iterate on solutions using real data, feedback, and operational constraints.
• Support the integration of analytics outputs into customer workflows, helping ensure solutions are practical, reliable, and adopted by users.
• Investigate deployment or operational issues and translate feedback into technical improvements.
• Present insights and recommendations clearly through reports, dashboards, workshops, and customer presentations.
• Support pre-sales and delivery activity through demos, business reviews, and occasional on-site customer engagement.
• Collaborate with Data Engineering, DevOps, and R&D teams to deploy, validate, and scale analytics solutions.
• Contribute to the continuous improvement of models, data workflows, and delivery processes.

Do you have experience in SciPy?, You have 2+ years of experience, working as a Data Scientist, Analytics Specialist, or in a similar role.

• A degree in Data Science, Computer Science, Engineering, Mathematics, Physics, Chemistry, or a related discipline.
• Strong practical Python skills and experience with common data science libraries such as pandas, numpy, scipy, statsmodels, or scikit-learn.
• The ability to turn data into clear, actionable insights for both technical and non-technical audiences.
• Experience working with predictive modelling, ideally with time-series, sensor, manufacturing, or operational data.
• Familiarity with cloud platforms such as Azure and an understanding of APIs or production environments.
• Confidence working in customer-facing or consulting-style environments, with strong communication and collaboration skills.