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Data Scientist

Job in Leeds, West Yorkshire, ME17, England, UK
Listing for: Motia
Full Time position
Listed on 2026-09-17
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineering, Data Scientist, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 55000 - 90000 GBP Yearly GBP 55000.00 90000.00 YEAR
Job Description & How to Apply Below

About us

At Motia, we’re at the forefront of fleet solutions, providing innovative services that power businesses across the UK. We’re committed to creating an environment where everyone can thrive. Our culture fosters collaboration, innovation, and growth, ensuring you can build a career, not just a job. With over 300 employees across five offices, we support over 55,000 customers nationwide.

About the role

Reporting to the Head of Business Intelligence, the Data Scientist will work across the full data lifecycle, developing advanced models, building scalable data solutions, contributing to the businesses data and AI strategy and helping shape our modern data platform as we transition to Microsoft Fabric.

Duties & Responsibilities
  • Partner with stakeholders across the company to understand business priorities, identify opportunities to create measurable customer and business value, and develop data science roadmaps that support strategic objectives.
  • Drive impactful outcomes for customers and the business by transforming complex data into actionable insights, recommendations and data products that enable objective decision-making with speed and confidence.
  • Promote and champion a data-driven culture by applying advanced analytics, statistics, machine learning, AI, and emerging technologies to solve business problems, improve performance and help the organisation move from reactive reporting to proactive and predictive decision-making.
  • Design, develop, deploy and continuously improve predictive, propensity and optimisation models that support customer acquisition, retention, cross-sell, customer lifetime value and margin optimisation.
  • Challenge existing ways of working by exploring new methodologies, technologies and AI-driven capabilities, identifying opportunities to improve efficiency, scalability and business outcomes.
  • Contribute to the evolution of the organisation's data platform, supporting the implementation and adoption of Microsoft Fabric and helping to establish modern, scalable and trusted data science, engineering and analytics capabilities.
  • Work collaboratively with Data Engineering to identify, integrate and ope rationalise valuable internal and external data sources, ensuring high standards of data quality, governance, accessibility and trust.
  • Support the design and development of data pipelines, APIs, data integrations and reusable data assets that enable advanced analytics, machine learning and self-service data capabilities within the Microsoft Fabric ecosystem.
  • Create and maintain clear, high-quality documentation for models, methodologies, datasets and projects, ensuring transparency, reproducibility and effective knowledge sharing across teams.
  • Work closely with Business Intelligence and Reporting teams to deliver intuitive dashboards, visualisations and data products that effectively communicate insights, recommendations and commercial impacts to technical and non-technical stakeholders.
Qualifications
  • Proven experience working as a Data Scientist or in a similar analytical role, preferably within the fleet industry
  • Strong proficiency in programming languages including Python, R and SQL for data manipulation, analysis, and modelling
  • Strong commercial acumen, able to contribute directly to overall business strategy and identify opportunities for models and technical solutions to solve commercial problems
  • Strong understanding of statistical analysis, machine learning techniques, and optimisation algorithms
  • Experience with data visualisation tools such as Qlik, Power BI, or Matplotlib for presenting insights and findings is preferable
  • Experience working with Microsoft Fabric, with an understanding of modern data platforms, lakehouse architectures, data engineering, analytics and AI…
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