Associate Data and AI Engineer

The Hartford•Columbus, OH

About The Position

The Claims Data Science team is committed to exploring new ways to use data and analytics to solve business problems within the Workers Comp, Employee Benefits, Auto, Property and General Liability claims domains. The team utilizes broad sources of data, both internal and external, to prevent fraud, enhance claim outcomes, and improve customer experience. We are passionate about technology and building well architected AI solutions that drive business value for our customers. As an Associate Data and AI Engineer, you will be a key contributor by partnering closely with other experts to design, develop, and implement AI assets for a wide range of new initiatives.

Requirements

Bachelor’s degree in Computer Science, Engineering, IT, Management Information Systems, or a related discipline
Experience developing solutions using Python and SQL, and using AI code assistants as part of daily workflow
Familiarity working with Github
Familiarity working in an Agile team
Exposure to data ingestion from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON
Exposure to ETL concepts, metadata management and data validation
Exposure to Automation tools (Autosys, Cron, Airflow, etc.) required
Able to communicate effectively with both technical and non-technical teams
Able to translate complex technical topics into business solutions and strategies
Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Nice To Haves

Exposure to GCP or AWS Services (i.e. S3, EMR, etc.) a plus
Exposure to Cloud Formation, Terraform, TeamCity, Jenkins, Octopus and other IAC tools and platform a plus
Exposure to Cloud data warehouses, automation, and data pipelines (i.e. Snowflake, Redshift) a plus

Responsibilities

Implementing data pipelines that bring together structured, semi-structured and unstructured data to support Predictive, AI and Agentic solutions.
Build and maintain scalable and robust AI-driven systems using technologies such as Snowflake, REST API’s, Apache Kafka, AWS Kinesis, Spark streaming, or similar.
Collaborate with external partners such as Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams.
Translate business requests into technical requirements for small and medium complexity engineering tasks.
Validate internal and external data sources for availability and quality when asked.
Work with SMEs to describe and understand data lineage and suitability for a use case
Assist in developing code that enables real-time modeling solutions to be ingested into front-end systems
Produce code artifacts and documentation using GitHub for reproducible results and hand-off to other teams if needed.
Ensure the reliability, availability, and scalability of AI solutions and systems through effective monitoring, alerting, and incident management.
Collaborate closely with AI Ops and infrastructure teams to ensure seamless deployment, operation, and maintenance of AI / ML systems.