Data Scientist, AI Studio (ML)

Job Title: Data Scientist, AI Studio (ML) Location: New York, NY; Boston, MA; Holmdel, NJ; or Bethlehem, PA

About The Company We are on a transformation journey to evolve into a modern, forward-thinking insurance company committed to enhancing the wellbeing of our customers and their families. Our AI team spearheads a culture of intelligence and automation across the enterprise, creating business value from advanced data and AI solutions. Our team includes data scientists, engineers, analysts, and product leaders working together to deliver AI-driven products that power growth, improve risk management, and elevate customer experience.

Job Summary We are looking for a Data Scientist, AI Studio to join our AI team in New York, Boston, Holmdel, or Bethlehem. The ideal candidate will be an experienced individual contributor with a strong background in data science & machine learning and a track record of turning advanced research into practical, impactful enterprise solutions. This role will involve building, deploying, and scaling ML models and intelligent automation solutions that reshape how we operate, serve customers, and drive growth. You’ll collaborate directly with senior executives and cross-functional teams on high-visibility projects to bring next-generation ML to life across our products and services.

Key Responsibilities

• Design and implement machine learning solutions: Automate business workflows, improve decision-making, and enhance customer and employee experiences through ML-driven solutions.
• Apply ML techniques to business data: Use regression, classification, clustering, ensemble methods (Random Forest, XGBoost) on structured and semi-structured data such as claims, underwriting notes, and customer records.
• Develop production-ready ML models: Build robust, scalable models that integrate with our platforms to deliver measurable business outcomes.
• Collaborate with technical teams: Partner with data engineers and MLOps teams to ensure models are scalable, robust, and production-ready.
• Translate research into practical applications: Apply machine learning and statistical modeling to underwriting, claims automation, customer servicing, and risk assessment.
• Work with cross-functional stakeholders: Partner with product owners, engineers, and business stakeholders to define use cases, design solutions, and measure impact.
• Build reusable ML frameworks: Contribute to developing components and frameworks for ML solution development and deployment.
• Maintain model governance: Adhere to documentation, testing, and best practices in partnership with key stakeholders.

Requirements

• Education: 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
• Experience: 2+ years of hands-on experience in ML modeling and development

• Skills:

• 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 machine learning techniques (regression, classification, clustering, ensemble methods) 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)

• Other: Passionate about applying machine learning to solve real-world business challenges; curious about new ML techniques; hands-on builder who enjoys moving solutions from prototype to deployment; comfortable collaborating in cross-functional teams and aligning technical solutions with business goals

Preferred Qualifications Experience in insurance, financial services, or related industries is a plus

Benefits

• Competitive Salary: $130,000 - $160,000