Quantitative Analyst

3 days ago


New York, New York, United States Inizio Partners Full time

About Inizio Partners

Inizio Partners is a leading organization in the industry, and we're looking for a skilled Quantitative Analyst to join our team. This role will play a crucial part in developing and applying models and statistical analysis within our enterprise data science group.

The ideal candidate will work closely with our cross-functional project teams to deliver repeatable and scalable data solutions that drive value for the organization. This includes understanding machine learning and deep learning models, applying them to optimize marketing efforts, and identifying areas where models may be less predictive.

This position requires a strong background in quantitative fields, such as Statistics, Mathematics, Computer Science, or Economics. A bachelor's degree is required, and advanced degrees are strongly preferred. The successful candidate will have 2+ years of experience in statistical modeling and quantitative analysis.

We offer a competitive salary of $120,000 - $150,000 per year, depending on experience. Our benefits package includes comprehensive health insurance, a 401(k) matching program, and generous paid time off.

Responsibilities:

  • Develop and apply 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 business context of projects and ability 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


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