Data Scientist

Guardian Life

Data Scientist developing Agentic AI and intelligent automation at Guardian. Collaborating with teams to enhance customer experience and drive business outcomes through AI advancements.

Posted 4/16/2026full-timeNew York City • Massachusetts, New Jersey, New York, Pennsylvania • 🇺🇸 United StatesJuniorMid-Level💰 $95,170 - $156,355 per yearWebsite

Tech Stack

Tools & technologies

PythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design and implement Agentic AI solutions that automate business workflows, improve decision-making, and enhance customer and employee experiences
Apply LLMs and generative AI to process and interpret unstructured data such as contracts, underwriting notes, claims, medical records, and customer interactions
Develop autonomous agents and reasoning systems that integrate with Guardian’s platforms to deliver measurable business outcomes
Collaborate with data engineers and AIOps teams to ensure models are scalable, robust, and production-ready
Translate research in agentic AI and reinforcement learning 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 the Data Science Lab by building reusable components and frameworks for developing and deploying agentic AI solutions

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 AI/ML modeling and development
Solid understanding of probability, statistics, and machine learning fundamentals
Strong programming skills in Python and familiarity with frameworks like PyTorch, TensorFlow, and LangGraph
Experience with LLMs, generative AI, and multi-step reasoning systems
Working knowledge of core software engineering concepts (version control with Git/GitHub, testing, logging, ...)
Working knowledge of a variety of machine learning techniques (clustering, decision tree, bagging/boosting artificial neural networks, etc.) and their real-world advantages/drawbacks
Strong communication skills and ability to collaborate effectively with product and engineering teams

Benefits

Comp & perks

Contemporary, supportive, flexible, and inclusive benefits
Skill-building opportunities
Leadership development
Philanthropic opportunities
Opportunities to build communities and grow your career

ATS Keywords

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Applicant Tracking System Keywords

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

Hard Skills & Tools

AI/ML modelingPythonPyTorchTensorFlowLangGraphprobabilitystatisticsmachine learningclusteringdecision tree

Soft Skills

strong communicationcollaboration

Certifications

PhDMaster's degreeBachelor's degree