Insight Global is looking for a Data Engineer to join one of our largest life insurance clients' Enterprise Data & Analytics engineering team. The ideal candidate will work closely with the Data Science team to enable cutting-edge AI and machine learning solutions that will contribute to enhancing customer well-being, fostering growth, maintaining competitive advantage, and customer satisfaction. The role requires a passion for data engineering, machine learning, and data-driven decision-making, and the ability to transform innovative ideas into tangible solutions that directly impact the business and customers. The Data Engineer will work in an innovative, fast-paced environment, collaborating with bright minds while enjoying a balance between strategic and hands-on work. The role offers opportunities for continuous learning and skillset expansion, mastering new tools and technologies that advance the companys goals. If you are a committed team player who thrives on creating value through innovative solutions and is eager to make a significant impact, this role could be a great fit for you.
Collaborate with data scientists and analysts to understand data requirements and translate them into scalable, high-performing data pipeline solutions.
Support data discovery and preparation for model development, perform detailed analysis of raw data sources by applying business context, and collaborate with cross-functional teams to transform raw data into curated and certified data assets to be used for machine learning and business intelligence use cases.
Extract text data from various sources like documents, logs, text notes stored in databases, and web pages using web scraping methods to support the development of natural language processing and language learning models.
Monitor and troubleshoot data pipeline performance, identifying and resolving bottlenecks and issues.
Collaborate with data science and data engineering teams to build scalable and reproducible machine learning pipelines for training and inference.
Implement machine learning models into operations and processes via batch, streaming, and API methods.
Develop, test, and maintain robust tools, frameworks, and libraries that standardize and streamline the data and machine learning lifecycle.
Contribute to developing and maintaining end-to-end MLOps lifecycle to automate machine learning solutions development and delivery.
Implement a robust monitoring framework for model performance.
Collaborate with cross-functional teams of Data Science, Data Engineering, business units, and various IT teams.
Create and maintain effective documentation for projects and practices, ensuring transparency and effective team communication.
Stay up-to-date with the latest trends in modern data engineering, machine learning, and AI, ensuring that our company remains at the cutting edge of industry advancements.
Location: New York, NY
Posted: Aug. 26, 2024, 1:46 a.m.
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