About the mission
We are looking for a Senior Data Science Analyst to design and implement a modular machine learning framework. The role involves developing machine learning models, managing data processes, and coaching team members, with a hybrid work arrangement.
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Description
The consultant is responsible for designing and setting up a modular and future-oriented machine learning framework.Key Responsibilities:
Implementing best practices for data preprocessing, model training, validation, and deployment
Integrating maintenance and feedback mechanisms (monitoring model performance, retraining)
Managing version control and reproducibility of models
Visualizing and sharing results
Providing logging and monitoring of the system
Preparing the infrastructure for migration to cloud environments
Documenting processes and procedures
Coaching and supporting team members in using the framework
Presenting analyses and results to business stakeholders
The consultant also develops and applies machine learning models to support business use cases.
Additional Responsibilities:
Translating business questions into technical solutions in iterative development cycles
Identifying and validating data sources
Performing data analysis and data preparation
Performing feature engineering to create relevant variables
Conducting exploratory data analysis (EDA) to evaluate data quality and patterns
Selecting and evaluating suitable algorithms
Developing, comparing, and tuning predictive models
Automating the model development process
Visualizing and presenting results in a clear and convincing manner
Continuously evaluating and optimizing models
Languages:
One of the two national languages is the mother tongue. The other national language must be read and understood.Additional Info:
The consultant comes to the office 2 days a week. On the other days, they can work remotely. The interview will be combined with a practical assignment.What you'll do
- Implement best practices for data preprocessing, model training, validation, and deployment
- Integrate maintenance and feedback mechanisms (monitoring model performance, retraining)
- Manage version control and reproducibility of models
- Visualize and share results
- Provide logging and monitoring of the system
- Prepare infrastructure for migration to cloud environments
- Document processes and procedures
- Coach and support team members in using the framework
- Present analyses and results to business stakeholders
- Translate business questions into technical solutions in iterative development cycles
- Identify and validate data sources
- Perform data analysis and data preparation
- Perform feature engineering to create relevant variables
- Conduct exploratory data analysis (EDA) to evaluate data quality and patterns
- Select and evaluate suitable algorithms
- Develop, compare, and tune predictive models
- Automate the model development process
- Visualize and present results in a clear and convincing manner
- Continuously evaluate and optimize models
What we're looking for
- Experience in implementing best practices for data preprocessing, model training, validation, and deployment
- Ability to integrate maintenance and feedback mechanisms
- Experience in managing version control and reproducibility of models
- Skills in visualizing and sharing results
- Knowledge in preparing infrastructure for cloud migration
- Ability to document processes and procedures
- Experience in coaching and supporting team members
- Ability to present analyses and results to stakeholders
Skills
- Azure ML SDK
- Jupyter Notebook
- Analytical models knowledge
- KNIME
- Machine learning and AI techniques
- Microsoft Azure Machine Learning
- Microsoft DevOps or similar
- Microsoft Fabric
- Microsoft SQL database
- Oracle Database administration
- Python as a data scientist
- SQL