Overview
We are seeking a Senior Data Scientist to join a collaborative team dedicated to developing and implementing analytical solutions for leading organizations globally. The successful candidate will take ownership of the entire solution lifecycle, from defining problems and designing models to their deployment, monitoring, and continuous improvement. This role involves tackling complex quantitative challenges and translating data into actionable insights that support strategic decision-making across various industries.
Responsibilities
- 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.
- Contribute to CI/CD pipelines, code quality standards, and engineering best practices.
- Communicate analytical findings and recommendations to both technical and non-technical stakeholders.
Requirements
- 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.