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