We are seeking a Data Scientist, an experienced individual contributor with strong background in data science & machine learning and a track record of turning advanced research into practical, impactful enterprise solutions. This role focuses on building, deploying, and scaling ML models and intelligent automation solutions that reshape how Guardian operates, serves customers, and drives growth. You'll collaborate directly with senior executives and cross-functional teams on high-visibility projects to bring next-generation ML to life across Guardian's products and services.
You Will:Key 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.
You are: - Passionate about applying machine learning to solve real-world business challenges.
- Curious about new ML techniques and their practical applications in industry.
- A hands-on builder who enjoys moving solutions from prototype to deployment.
- Comfortable collaborating in cross-functional teams and aligning technical solutions with business goals.
- An effective communicator, able to present complex ideas and trade-offs to both technical and non-technical stakeholders.
You have: - 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.
Salary Range:$95,170.00 - $156,355.00
The salary range reflected above is a good faith estimate of base pay for the primary location of the position. The salary for this position ultimately will be determined based on the education, experience, knowledge, and abilities of the successful candidate. In addition to salary, this role may also be eligible for annual, sales, or other incentive compensation.
Our PromiseAt Guardian, you'll have the support and flexibility to achieve your professional and personal goals. Through skill-building, leadership development and philanthropic opportunities, we provide opportunities to build communities and grow your career, surrounded by diverse colleagues with high ethical standards.
Inspire Well-BeingAs part of Guardian's Purpose - to inspire well-being - we are committed to offering contemporary, supportive, flexible, and inclusive benefits and resources to our colleagues. Explore our company benefits at www.guardianlife.com/careers/corporate/benefits. Benefits apply to full-time eligible employees. Interns are not eligible for most Company benefits.
