Expert Data Scientist Role
The ideal candidate will possess a strong background in machine learning, with expertise in designing and implementing modular, future-proof frameworks. Key responsibilities include defining and implementing best practices for data preprocessing, model training, validation, and deployment, as well as ensuring robust version control and logging across the ML infrastructure.
Key Responsibilities:
* Design and implement a Machine Learning framework that meets business needs in an agile and iterative manner.
* Define and implement best practices for data preprocessing, model training, validation, and deployment.
* Integrate model monitoring, maintenance, and feedback loops to track performance and retrain models.
* Prepare infrastructure for potential migration to cloud environments.
* Provide documentation of all processes and components.
Development and Application of Machine Learning Models:
* Translate business questions into ML solutions through iterative collaboration.
* Identify, assess, and prepare relevant data sources.
* Conduct data exploration, feature engineering, and data quality assessments.
* Select appropriate algorithms and develop, compare, and tune predictive models.
* Automate modeling workflows and present results in a clear and impactful manner.
Technical Skills:
* Machine Learning Techniques & Analytical Modeling (expertise required).
* Python for data science.
* SQL (expert).
* Microsoft Azure Machine Learning / Azure ML SDK.
* Microsoft DevOps or similar.
* Microsoft Fabric.
* Jupyter Notebooks.
* Microsoft SQL Database.
* Oracle Database Management.
Soft Skills:
* Strong analytical thinking and communication skills.
* Ability to clearly explain technical concepts to business users.
* Proactive and autonomous mindset.
* Ability to coach team members and work collaboratively.