MLOps Catastrophe & Geo-Analytics at Mercury Insurance Services, LLC

United States

$94.458k - $179.048k

Overview Join an amazing team that is consistently recognized for our achievements and culture, including our most recent Forbes award of being one of America's Best Midsize Employers for 2026! Position Summary: 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. Geo-Salary Information An in-person interview may be required during the hiring process State specific pay scales for this role are as follows: $94,458 to $179,048 (NJ, NY, WA, HI, AK, MD, CT, RI, MA) $85,871 to $162,771 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME) $77,283 to $146,494 (UT, ID, MT, NM, SD, NE, KS, OK, IA, AR, LA, MS, AL, TN, KY, IN, SC, NC, WV) In CA: Typical hiring range is $123,077.70 to $170,941.25 The expected base salary for this position will vary depending on a number of factors, including relevant experience, skills and location. Responsibilities Essential Job Functions: 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 Qualifications Education: Minimum: 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 Preferred: Master’s degree Experience: Minimum: 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 Preferred: 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) Knowledge and Skills: 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 About the Company Why choose a career at Mercury? At Mercury, we have been guided by our purpose to help people reduce risk and overcome unexpected events for more than 60 years. We are one team with a common goal to help others. Everyone needs insurance and we can’t imagine a world without it. Our team will encourage you to grow, make time to have fun, and work together to make great things happen. We embrace the strengths and values of each team member. We believe in having diverse perspectives where everyone is included, to serve customers from all walks of life. We care about our people, and we mean it. We reward our talented professionals with a competitive salary, bonus potential, and a variety of benefits to help our team members reach their health, retirement, and professional goals. Learn more about us here: https://www.mercuryinsurance.com/about/careers Perks and Benefits We offer many great benefits, including: 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 Mercury Insurance is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by federal, state, or local law. Pay Range USD $94,458.00 - USD $179,048.00 /Yr.