Design and build scalable solutions to ingest, store and process very large amounts of data (structured, semi-structured and unstructured), including streaming and real-time into the cloud-based Lakehouse & cloud data warehouse.
Take ownership of operationalization of Agentic AI flows while designing solutions to optimize data pipelines, model deployment, and model monitoring
Architect blueprints for production grade, scalable end-to-end Data & AI solutions
Lead the integration of LLMs, lang chain, lang graphs, agent orchestrators into business processes
Build enterprise grade, highly reusable data assets for analytics consumption.
Partner with analytics experts, data scientists, and Business Unit analysts to build self-service experiences in our data democratization platform.
Innovate different ways of combining data sets from various sources to augment our analytical literacy.
Conduct POCs, Pilots on re-usable, 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.
Work closely with the IT and the cloud infrastructure teams to deliver technical solutions.

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
Ability to work in a fast-paced environment as a technical lead
Strong software standards and engineering practices working within a shared codebase
Experience in building enterprise grade Data & AI solutions within commercial insurance or financial services industry.
Experience in ELT capabilities (Data Factory, DBT, Five Tran etc.) and languages such as Python, R, Scala, Java, and SQL.
Experience with various Microsoft Azure services (including Data Lake, Databricks, Data factory, Cosmos DB, Power Platform, Co-pilot studio, Azure ML, Power Automate, Power BI etc.).
Experience with vector stores like Elastic, Pinecone, Mongo Atlas, or Redis
Experience with cloud data warehouse solutions like Snowflake, Fabric, or Redshift
Exposure to deployments for LLMs including end to end unstructured data pipeline build, design of vector stores, embeddings, and prompt engineering.
Strong communication skills with ability to effectively explain complex material

Benefits

Competitive pay
Comprehensive benefits for employees and their families

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Predictive AnalyticsData ProcessingData CurationModel DeploymentModel MonitoringData Pipeline OptimizationComputer VisionDeep LearningELTSoftware Engineering Practices

Soft Skills

Technical LeadershipCommunicationCollaborationProblem SolvingAdaptability

Certifications

Bachelor’s Degree in MathematicsZurich Certified Insurance ApprenticeAssociate Degree in Mathematics