IND Staff Engineer - GCC094 We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.

Responsibilities

Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies. Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage. Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations. Accountable for design, development and maintenance of Models as Service Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences. Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams Delivery of critical milestones for model deployment in the AWS and GCP clouds. Adopt and promote MLOps best practices to the Data Science community. Minimum

Requirements

Development experience using both the AWS and GCP suite of tools. Familiarity with SageMaker, Streamlit, web security, credentials and API management tools

Experience

developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns.

Experience

building and deploying webservices in a cloud environment.

Experience

building CICD pipeline using Jenkins or equivalent

Experience

with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or similar Expert-level Github experience, including Github Actions Strong object oriented development experience using Python, Java, C# Familiarity with big data technologies (i.e. Hadoop, Spark, Hive, etc.) and RDBMS platforms such as Redshift, Snowflake or BigQuery

Experience

in end to end model development lifecycle, from ideation through post production monitoring.

Experience

with workflow automation platforms (Apache Airflow, Autosys, similar)

Experience

with Solution Design and Architecture of data pipelines Basic understanding of Data Science model development life cycle Preferred Skills Fundamentally strong with Data Structures and algorithms.

Experience

working with Docker, Kubernetes and EC2 environment.

Experience

building ML and data pipeline and orchestration services Basic understanding of ML frameworks i.e. Tensorflow, Anacoda, Scikit Learn,

Experience

working in an Agile framework.

Qualifications

ML engineering, data manipulation and application development Python development experience Working with IAC, developing CICD pipelines

Experience

in the insurance or broader financial services industry SQL development experience Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM’s into automated processes

About Us

| Our Culture | What It’s Like to Work Here Every day, a day to do right. Showing up for people isn’t just what we do. It’s who we are – and have been for more than 200 years. We’re devoted to finding innovative ways to serve our customers, communities and employees—continually asking ourselves what more we can do. Is our policy language as simple and inclusive as it can be? Can we better help businesses navigate our ever-changing world? What else can we do to destigmatize mental health in the workplace? Can we make our communities more equitable? That we can rise to the challenge of these questions is due in no small part to our company values that our employees have shaped and defined. And while how we contribute looks different for each of us, it’s these values that drive all of us to do more and to do better every day.

About Us

Our Culture What It’s Like to Work Here Perks &

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