Responsibilities:

• Analyze and perform Exploratory Data Analysis (EDA) on raw datasets
• Develop visualizations to present key findings from EDA
• Identify potential machine learning (ML) or Large Language Model (LLM) opportunities that drive business value
• Cleanse and prepare data for ML model development
• Engineer features that might improve performance of models
• Perform hypothesis testing to determine feasibility of a ML or LLM application
• Plan and execute the model life cycle management using MLOps

Minimum Qualifications:

• Bachelor’s degree in a quantitative field engineering, computer science, mathematics, statistics, or data science
• Relevant class or work experience proving the ability to apply advanced analytics techniques to real-world problems
• Understanding of standard data science practices

• Strong written and verbal communication skills
• Ability to be effective in a team environment

• Curiosity and enthusiasm to learn new domains
• Knowledge of Python or R and SQL

Preferred Qualifications:

• Experience with Big Data platforms, such as Spark, would be advantageous
• Experience with MLOps, specifically MLflow, are a plus
• Experience with distributed cloud providers such as Microsoft Azure, AWS, or GCP are a plus