MLOps Catastrophe & Geo-Analytics

Mercury Insurance Services, LLC•Remote,

1d•$94,458 - $179,048•Remote

About The Position

As an MLOps Catastrophe Modeling & Geo-Analytics, you'll be a member of a team dedicated to productionizing machine learning models and systems, including the implementation of data science pipeline orchestration and automation. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging state-of-the-art technology platforms. You’ll serve as a major technical contributor, writing and reviewing model and application code, as well as ensuring high availability and performance of our batch, API, and streaming machine learning applications. You'll have the opportunity to continuously learn & apply the latest innovations and best practices in machine learning engineering.

Requirements

Bachelor's degree in Computer Engineering, Computer Science, Mathematics, Electrical Engineering, Information Systems, or related technical field Or equivalent combination of education and/or experience
2 or more years of experience in MLOps engineering, data engineering, data science, and/or software engineering
2 or more years experience in writing SQL
2 or more years experience in writing Python
Experience working with various stakeholders from different backgrounds
Experience at analyzing data, systems, and processes to identify gaps and inconsistencies
Able to multitask, prioritize, and manage time effectively
The ability to think conceptually, analytically and creatively; comfortable with ambiguity
Experience managing and communicating plans to peers and with internal partners
Demonstrated solid understanding, and passion for, multiple areas of MLOps engineering best practices
Experience in SQL programming
Experience in Python
Experience with cloud-based advanced data and analytics environment (e.g., AWS)
Experience with GitHub and/or GitLab
Proficient data skills and the ability to work with large structured and unstructured data sources
Excellent problem-solving skills required
Excellent analytical and critical thinking required
Excellent written and verbal communication skills required
Demonstrate Company’s Core Values

Nice To Haves

Master’s degree
Experience in P&C insurance or broader financial services industry
Experience in modeling with Verisk, Touchstone, and or RMS
Experience building models and processes as code
Experience working with discrete global grid systems(like H3 or S2)

Responsibilities

Develop and use modern software engineering practices to deploy ML solutions at scale, including building CI/CD pipelines and automated testing.
Work with Data Scientists and Data Engineers to build automated pipelines that train, run and monitor ML Models for business applications in an agile and elegantly orchestrated manner
Enhance and improve the code deployment and model monitoring frameworks and project operations documentation
Support life cycle management of deployed ML model life cycle management (e.g. new releases, change management, monitoring and troubleshooting)
Support the MLOps Platform, including model registry, model deployment, and feature store.
Knowledge of cloud-based infrastructure and demonstrated ability to architect scalable and extensible services.
Collaborate with expert vendors and IT application teams for integrating ML models including defining SLAs and designing highly automated end-to-end testing
Other functions may be assigned

Benefits

Competitive compensation
Flexibility to work from anywhere in the United States for most positions
Paid time off (vacation time, sick time, 9 paid Company holidays, volunteer hours)
Incentive bonus programs (potential for holiday bonus, referral bonus, and performance-based bonus)
Medical, dental, vision, life, and pet insurance
401 (k) retirement savings plan with company match
Engaging work environment
Promotional opportunities
Education assistance
Professional and personal development opportunities
Company recognition program
Health and wellbeing resources, including free mental wellbeing therapy/coaching sessions, child and eldercare resources, and more