Data Scientist, AI Studio

Guardian Life

Data Scientist driving AI solutions for Guardian's insurance business. Collaborating on ML model development to enhance customer experiences and business workflows.

Posted 7/17/2026full-timeNew York City • New York • 🇺🇸 United StatesJuniorMid-Level💰 $95,170 - $156,355 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing machine learning solutions, with a strong foundation in statistical modeling and programming in Python. Capable of collaborating with cross-functional teams to translate complex ML concepts into practical applications that drive business outcomes.

Highest-signal resume keywords

Machine Learning ModelingPython ProgrammingStatistical AnalysisCollaboration with Cross-Functional TeamsModel Governance and Best Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning TechniquesRegressionClassificationClusteringEnsemble MethodsRandom ForestXGBoostProbabilityStatisticsML Model Development

Soft Skills

Problem-SolvingAnalytical SkillsAttention to DetailCommunication Skills

Tools & Technologies

Scikit-learnPandasNumpyGitGitHub

Industry Keywords

InsuranceFinancial ServicesBusiness WorkflowsRisk AssessmentCustomer Servicing

Tech Stack

Tools & technologies

NumpyPandasPythonScikit-Learn

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

opportunities to build communities and grow your career
diverse colleagues with high ethical standards