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Guardian Life · 1 day ago

Data Scientist, ML - Insurance Underwriting

New York, NY

Full-time

Hybrid

Entry, Mid Level

$95K/yr - $156K/yr

2+ years exp

Guardian Life is on a transformation journey to evolve into a modern insurance company focused on enhancing customer wellbeing. They are seeking a Data Scientist specialized in Machine Learning to design and implement AI-driven solutions that automate workflows and improve decision-making across their operations.

DentalFinancial ServicesHardwareInsuranceLife Insurance

No H1B

Responsibilities

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

Qualification

Machine LearningPythonStatistical ModelingInsurance Industry ExperienceData Engineering CollaborationML TechniquesSoftware Engineering ConceptsProblem-Solving SkillsCommunication SkillsAttention to Detail

Required

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)