Responsibilities:
- Specialize in Data Collection, Transformation, and Modeling: Extract, clean, and analyze diverse data, applying statistical and machine learning techniques for predictive modeling.
- Feature Engineering and Selection: Identify and engineer features for enhanced model efficiency and interpretability.
- Model Building and Continuous Improvement: Develop, implement, and refine machine learning models to solve business problems, focusing on automation and ongoing enhancement.
- Effective Communication through Visualization: Utilize tools such as Power BI or Matplotlib/Plotly to create compelling visualizations for clear communication with stakeholders.
Requirements:
- Relevant academic or professional experience in the data science or data engineering space
- Knowledge of data engineering and data science in general with demonstrable practical skills Required:
- Python proficiency – Pandas, Tensorflow/ Keras/ PyTorch, Matplotlib/Plotly
- SQL
- Azure Machine Learning Studio, Azure Dev Ops, Azure Functions, Docker
Advantageous:
- Azure Data Factory
- Azure Data Lake (Blob storage)
- Synapse Data Warehouse (Dedicated SQL Pools)
- Self-sufficient in working through analytical projects from idea to results phases
- Experience working with Git, automation of ML pipelines and endpoints
Education:
Bachelor’s Degree or higher in Engineering, Information Technology, or related field