Description

You will develop and implement machine learning and deep learning models for prediction, classification, and clustering projects. You will apply machine learning or reinforcement learning to optimize marketing efforts, including customer acquisition, retention, pricing, and operations. You will translate complex business issues into achievable analytical learning objectives and actionable projects. You will identify areas where models have predictive caveats or limitations within a business context. You will communicate complex analytics results and practical business implications to multi-disciplinary teams. You will explore and apply latest AI techniques and large language model applications.

Responsibilities

• Develop and implement machine learning and deep learning models for prediction, classification, and clustering.
• Apply machine learning or reinforcement learning to optimize marketing efforts.
• Translate complex business issues into achievable analytical learning objectives.
• Identify predictive caveats or limitations within a business context.
• Communicate complex analytics results and practical business implications to multi-disciplinary teams.

Required Skills

• 2+ years of experience in statistical modeling and quantitative analysis.
• Proficiency with Python, including pandas and scikit-learn.
• Experience with Spark or PySpark.
• Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, Engineering, or Operations Research.
• Experience working in Linux environments.
• Knowledge of AWS.
• Experience with Git and Docker containers.
• Experience with Databricks, AWS SageMaker, or Azure AI Studio.

Preferred Skills

• Advanced Degree (MS or PhD) in Statistics, Mathematics, or Quantitative Marketing with a focus on machine learning.
• Experience in retail electricity or gas.

Key Skills

Education

Bachelor's degree in Computer Science