Data Scientist, Python – MLOps
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Job Description
Data Scientist focusing on deploying models into production, collaborating with stakeholders and leveraging Python and MLOps expertise. Enhancing data-driven solutions for financial and investment sectors.
Responsibilities:
- Collaborate closely with key stakeholders and a team of data scientists
- Design and implement new project code and MLOps frameworks for the deployment of models in production
- Build machine learning models for financial / investment company
- Partner with client teams to identify opportunities where data science could add value, helping generate demand and shape a roadmap for future work
- Monitor existing productionised pipelines, addressing any issues in a timely manner to ensure smooth and continuous operation
Requirements:
- Thorough knowledge of the Python language
- Experience in training, tuning and refining ML models in Python (mainly scikit learn and tree based models) (Core ML)
- Working understanding of end to end machine learning pipelines
- MLOps and DevOps frameworks
- Daily use of GitHub, including version control, collaboration, testing and CI/CD
- Superb written and verbal communication skills and demonstrated ability to communicate complex technical and statistical ideas to non-specialists effectively
- Experience in cloud platforms such as Azure, AWS, and Databricks (Fabric / Azure nice to have)
- Nice to have: Financial / Investment understanding, experience with cashflow & pricing models.
Benefits:
- People are at the Heart of our Business. By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive.
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