GenAI Solutions Architect

Zurich Insurance - Schaumburg, IL

Full-time - Mid Level

Remote - Schaumburg, IL

Insurance Carriers and Related Activities

About the position

The Data & Analytics department is seeking a GenAI Solutions Architect to spearhead the development and execution of technical capabilities within the GenAI solutions space. This role is pivotal in implementing the Data Analytics Strategy & Architecture across the Data Science, Data Governance, and Data Engineering teams. The architect will be responsible for constructing the architecture, systems, and technologies necessary to establish a best-in-class data ecosystem. The ideal candidate will work in a hybrid schedule at the Schaumburg North America HQ, focusing on next-generation analytics capabilities and processes that support various Business Units and Service Units. The GenAI Solutions Architect will innovate methods to combine data sets from diverse sources to enhance analytical literacy. Responsibilities include conducting proof of concepts (POCs) and pilots on reusable, scalable data processing frameworks to eliminate point solutions. The architect will evaluate and optimize system resources for large-scale data processing, image processing, computer vision, and deep learning. They will design and build scalable infrastructure to ingest, store, and process vast amounts of data, including streaming and real-time data into a cloud-based Data Lake. Collaboration with Business Unit analysts is essential to create self-service experiences in the data democratization platform. Staying current with the latest advancements in AI, Machine Learning, Deep Learning, NLP, and Image Processing is crucial. The architect will take ownership of operationalizing AI processes, optimizing data pipelines, model deployment, and monitoring. Close collaboration with engineering and platform teams is required to deliver comprehensive technical solutions, including end-to-end data orchestration, data governance, and metadata management. Additionally, the architect will partner with various business groups for in-depth data analysis, including propensity scores, catastrophic modeling, time-series analysis, and forecasting.

Responsibilities

• Innovate different ways of combining data sets from various sources to augment analytical literacy.
• Conduct POCs and pilots on reusable, scalable data processing, curation, and consumption frameworks to eliminate point solutions.
• Evaluate, analyze, and optimize system resources related to large scale data processing, image processing, computer vision, and deep learning.
• Design and build scalable infrastructure and platform to ingest, store, and process very large amounts of data (structured, semi-structured, and unstructured), including streaming and real-time data into the cloud-based Data Lake.
• Work closely with Business Unit analysts to build self-service experiences in the data democratization platform.
• Stay current on the latest developments in AI, Machine Learning, Deep Learning, NLP, and Image Processing by reading relevant papers and journals, applying new learnings to create innovative data and analytics solutions.
• Take ownership of operationalizing AI processes while designing solutions to optimize data pipelines, model deployment, and model monitoring.
• Collaborate with engineering and platform teams to deliver technical solutions, including end-to-end data orchestration, data layering, data governance, metadata management, and data cataloging.
• Partner with data science, actuarial science, underwriting, claims, and various business groups on deep-rooted data analysis, including propensity scores, catastrophic modeling, time-series analysis, and forecasting.

Requirements

• Bachelor's Degree in Mathematics/Statistics and 7 or more years of experience in the Predictive Analytics area OR
• Zurich Certified Insurance Apprentice including an Associate Degree in Mathematics/Statistics and 7 or more years of experience in the Predictive Analytics area OR
• High School Diploma or Equivalent and 9 or more years of experience in the Predictive Analytics area.

Nice-to-haves

• Experience with large language models, end-to-end pipeline designs, and CI/CD frameworks.
• Experience with various Microsoft Azure services (including OpenAI, Data Lake, Synapse, Databricks, Data Factory, Cosmos DB, Power Platform, Azure ML, Power Automate, Power BI, etc.).
• Experience in ETL/ELT and data wrangling using tools (Informatica, Data Factory, Talend, etc.) and languages such as Python, R, Scala, Java, SQL, and SAS.
• Strong communication skills with the ability to effectively explain complex material.
• Ability to work in a fast-paced environment as a technical lead.
• Strong software standards and engineering practices working within a defined codebase.

Benefits

• Comprehensive employee benefits package for employees and eligible dependents.
• Ongoing career development opportunities.
• Diverse and inclusive work environment.
• Competitive compensation.