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Data Scientist, Contract

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Onsite

Data Scientist, Contract

Morgan Mckinley Limited

Data Scientist, Contract

Skills

SQL QueriesPythonData ScienceData VisualizationData AnalysisMachine LearningAIPower BI

2 months ago

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Important information


Contract type:

Freelance / Contract

Work mode:

Onsite

Published on:

18 August 2026

What they need


Responsibilities

  • Design, build, deploy, and maintain data science, machine learning, analytics, and AI-enabled solutions to improve sales/distribution effectiveness, productivity, and business decision-making.
  • Apply advanced analytical techniques to identify actionable insights, solve business problems, and support strategic initiatives.
  • Develop and maintain Power BI dashboards and reports, including data modelling and effective data visualisation.
  • Partner with stakeholders across business, sales, marketing, operations, and technology teams to translate business needs into practical data solutions.
  • Ensure the quality, consistency, and reliability of data from multiple internal and external sources.
  • Present analysis, recommendations, solution outcomes, and project updates clearly to senior stakeholders.
  • Support responsible use of data and AI by ensuring solutions align with relevant regulatory, privacy, risk, and internal governance requirements.
  • Monitor solution performance and continuously enhance models, dashboards, and analytics products based on business feedback and changing needs.

Requirements

  • Bachelor's degree or above in Statistics, Computer Science, Mathematics, Data Science or another quantitative discipline.
  • At least 5 years of relevant experience in data analytics, data science, machine learning, business intelligence, or related functions.
  • Strong hands-on Python and SQL skills, with experience building, implementing, and maintaining analytics or machine-learning solutions.
  • Solid experience with Power BI, including dashboard development, data modelling, DAX, and visualisation design.
  • Practical experience applying machine-learning techniques such as classification, regression, clustering, forecasting, recommendation engines, or propensity modelling.
  • Comfortable working with large and complex datasets, including data preparation, feature engineering, validation, and model-performance monitoring.
  • Exposure to generative AI, large language models, agentic AI, or intelligent automation tools, with an ability to identify and support practical business use cases.
  • Strong stakeholder-management and communication skills, with the ability to explain technical findings in a clear, business-focused manner.
  • Able to work independently, manage competing priorities, and deliver effectively in a fast-paced environment.
  • Experience in insurance or consultancy firm is a plus

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