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About the Role
This is an opportunity for a Senior Data Scientist to join a team focused on developing and deploying analytical solutions used by leading organizations worldwide. You'll enjoy taking ownership of the entire solution lifecycle, from problem definition and model design through to deployment, monitoring, and continuous improvement. You will work on complex quantitative challenges, helping transform data into actionable insights supporting strategic decision-making.
Client Details
Our client is a globally recognized provider of independent market intelligence, delivering data-driven insights and forecasts across countries, industries, and risk domains. They partner with leading organizations worldwide to support strategic decision-making in complex and evolving markets.
Description
- Design, develop, and deploy production-grade data science and machine learning solutions.
- Own the full delivery lifecycle from concept, data acquisition, and modeling through to deployment and operational support.
- Build robust, scalable, and maintainable Python applications suitable for enterprise environments.
- Develop forecasting models, predictive analytics solutions, and quantitative methodologies.
- Work closely with subject matter experts to translate analytical frameworks into defensible, repeatable outputs.
- Design and implement testing, validation, and monitoring processes to ensure model quality and reliability.
- Develop and maintain cloud-based and containerized analytical applications.
- Contribute to CI/CD pipelines, code quality standards, and engineering best practices.
- Communicate analytical findings and recommendations to both technical and non-technical stakeholders.
- Support ongoing enhancement of production systems, ensuring governance, reproducibility, and operational resilience.
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Profile
- Minimum 7 years' commercial experience in Data Science, Machine Learning, or Quantitative Development.
- Strong Python development skills with experience building production-ready applications.
- Proven experience delivering analytical solutions into live production environments.
- Strong understanding of statistical modeling, machine learning techniques, and model evaluation methodologies.
- Experience working with time series analysis, forecasting, classification, regression, and clustering techniques.
- Strong SQL and data manipulation skills.
- Experience with software engineering best practices, including testing, version control, and code reviews.
- Exposure to cloud platforms, containerization, and modern deployment practices.
- Knowledge of CI/CD, DevOps, or MLOps principles would be highly beneficial.
- Excellent communication skills and the ability to engage effectively with both technical and business stakeholders.
- Degree in a quantitative discipline preferred.
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Job Offer
- 6-month contract with strong potential for extension.
- 2-3 days per week in the London office (hybrid working).
- Competitive day rate (outside IR35).
- Opportunity to work on high-impact, real-world problems.
- Collaborative, intellectually stimulating environment with strong learning opportunities.
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