- Exposure to specifically large language models
- Previous Insurance industry experience
- Strong experience with python development building out data pipelines
- Strong experience with Pyspark
- Exposure to Databricks or other data warehouses
- Exposure to machine learning technologies and models should possess an understanding of how to implement model into a data environment
- Experience working in a cloud environment
- AWS preferred
Data Engineer - New York, United States - Insight Global
Description
Insight Global is seeking a Data Engineer (Machine Learning) to join one of their top insurance clients sitting in either NYC, Holmdel, NJ, or Bethlehem, PA.
This individual will be joining the Enterprise Data & Analytics Engineering team with the goal of implementing and enabling machine learning solutions into the existing data environment.
This individual will be responsible for building out additional data pipelines that will sustain large language models and additional machine learning techniques.
They'll work closely with Data Scientists who are creating each model for different business lines.The goal is to integrate more ML and AI techniques that will lead to highly processed and usable data, used by various lines of business throughout the enterprise.
We are seeking a strong Data Engineer with strong Python and Pyspark, who also has a strong understanding of machine learning best practices.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day.
We are an equal opportunity/affirmative action employer that believes everyone matters.Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.
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