Job description

Essential Duties/Responsibilities

  • Understanding of machine learning and deep learning models to select and implement for
  • prediction, classification, and clustering projects
  • Apply machine learning or reinforcement learning to optimize marketing efforts with respect to
  • customer acquisition, retention, pricing, cross-selling, operations and trading
  • Passion to learn latest AI techniques and explore applications for large language models
  • Understanding of the business context of projects and able to identify areas where models will be
  • less predictive or have caveats to their predictive powers
  • Ability to translate complex business issues into achievable analytical learning objectives and
  • actionable analytic projects
  • Ability to communicate and establish good relations with multi-disciplinary teams
  • Proficiency with Python, including pandas, scikit-learn
  • Experience in Spark or Pyspark

Minimum Requirements

  • Bachelor's degree in a quantitative field, such as Statistics, Mathematics, Computer Science,
  • Economics, Engineering, or Operations Research required.
  • 2+ years of experience in statistical modeling and quantitative analysis in industry or full-time
  • academic research

Preferred Qualifications

  • Advanced Degree (MS or PhD) in Statistics, Mathematics or Quantitative Marketing with a focus on
  • machine learning is strongly preferred.
  • Additional Knowledge, Skills and Abilities:
  • Experience with Databricks
  • Experience with AWS SageMaker
  • Experience with Azure AI Studio
  • Retail electricity or gas experience
  • Comfortable working in Linux
  • Experience with Git
  • Experience with Docker containers
  • Ability to learn and apply new quantitative techniques quickly and appropriately
  • Ability to interpret and communicate complex analytics results

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