Data Scientist - Customer Focus

Are you passionate about transforming complex data into actionable insights? Do you thrive on solving real-world operational challenges with innovative analytics? If so, this is an exceptional opportunity to advance your career at a leading organisation that operates at the cutting edge of data science and industrial technology.

Who They Are

Our Client specialises in developing advanced vacuum products and exhaust management systems that are vital to a variety of industries, from semiconductor manufacturing to scientific research. With a global presence and a reputation for innovation and quality, they are dedicated to fostering a culture of trust, continuous learning, and technological excellence. Working here means contributing to solutions that are essential in high-tech manufacturing and industrial processes worldwide.

The Opportunity

This strategic hire is driven by the organisation's commitment to leveraging data-driven insights to optimise performance and minimise operational downtime for its customers. As a Data Scientist with a customer-centric approach, you will be instrumental in delivering predictive models and analytics that directly impact customer success. This role offers a fascinating blend of technical challenge, client interaction, and tangible impact-ideal for professionals eager to shape the future of industrial analytics.

Your Key Responsibilities

• Analyse, prepare, and interpret data sets to develop predictive models that enhance equipment reliability and operational efficiency.
• Collaborate closely with customer teams and internal stakeholders to quickly develop and refine data solutions, adapting to operational feedback.
• Integrate analytics outputs into customer workflows, ensuring solutions are practical, reliable, and user-friendly.
• Investigate and resolve deployment issues, translating operational insights into technical enhancements.
• Clearly communicate findings and recommendations through reports, dashboards, and engaging presentations for diverse audiences.
• Support sales and project delivery by demonstrating analytical solutions, participating in business reviews, and engaging with clients during visits.
• Partner with Data Engineering, DevOps, and R&D teams to validate, deploy, and scale analytics tools across various environments.
• Contribute to ongoing improvements in models, data workflows, and delivery practices to optimise efficiency and impact.

• A minimum of two years' practical experience in data science, analytics, or a related field.
• A degree in Data Science, Computer Science, Engineering, Mathematics, Physics, Chemistry, or similar.
• Strong proficiency in Python and familiarity with core data science libraries such as pandas, numpy, scipy, statsmodels, or scikit-learn.
• Experience crafting predictive models, especially against time-series or operational sensor data.
• Knowledge of cloud platforms, preferably Azure, and a good understanding of APIs and production deployment environments.
• Excellent communication skills with the ability to convey technical insights clearly to non-technical audiences.
• Confidence working in client-facing or consultancy settings, demonstrating collaboration and problem-solving prowess.

Nice-to-Haves

• Experience with manufacturing, industrial, or sensor data analytics.
• Familiarity with other programming languages or analytics tools.
• Previous involvement in product deployment or operational environments.

• Access continuous professional development and career progression opportunities.
• Contribute to meaningful projects that have a real impact on manufacturing efficiency and industrial advancement.
• Enjoy comprehensive benefits, including flexible work options and support for health and well-being.

Ready to Make an Impact?

If you're eager to apply your data science expertise within a dynamic and impactful environment, we invite you to submit your CV today. Join our client's journey to drive industrial innovation through data-driven solutions, and become part of a global leader shaping the future of advanced manufacturing technology.

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