Design and implement machine learning solutions that automate business workflows, improve decision-making, and enhance customer and employee experiences
Apply ML techniques (e.g., regression, classification, clustering, ensemble methods such as Random Forest and XGBoost) to structured and semi-structured data such as claims, underwriting notes, and customer records
Develop robust, scalable, and production-ready ML models that integrate with Guardian’s platforms to deliver measurable business outcomes
Collaborate with data engineers and MLOps teams to ensure models are scalable, robust, and production-ready
Translate research in machine learning and statistical modeling into practical applications for underwriting, claims automation, customer servicing, and risk assessment
Work closely with product owners, engineers, and business stakeholders to define use cases, design solutions, and measure impact
Contribute to building reusable components and frameworks for developing and deploying ML solutions
Adhere to model governance, documentation, testing, and other best practices in partnership with key stakeholders

Requirements

PhD with 0–1 years of experience, Master’s degree with 2+ years, or Bachelor’s degree with 4+ years in Statistics, Computer Science, Engineering, Applied Mathematics, or related field
2+ years of hands-on experience in ML modeling and development
Solid understanding of probability, statistics, and machine learning fundamentals
Strong programming skills in Python and familiarity with frameworks like scikit-learn, pandas, and numpy
Experience with a variety of machine learning techniques (regression, classification, clustering, ensemble methods, etc.) and their real-world advantages/drawbacks
Excellent problem-solving and analytical skills with attention to detail
Strong communication skills and ability to collaborate effectively with product and engineering teams
Working knowledge of core software engineering concepts (version control with Git/GitHub, testing, logging, ...)
Experience in insurance, financial services, or related industries is a plus.

Benefits

Applicant Tracking System Keywords

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

machine learningregressionclassificationclusteringensemble methodsRandom ForestXGBoostPythonscikit-learnpandas

problem-solvinganalytical skillsattention to detailcommunication skillscollaboration

PhDMaster's degreeBachelor's degree