Senior Machine Learning Engineer

About the position

FM is a leading property insurer of the world's largest businesses, providing more than one-third of FORTUNE 1000-size companies with engineering-based risk management and property insurance solutions. FM helps clients maintain continuity in their business operations by drawing upon state-of-the-art loss-prevention engineering and research; risk management skills and support services; tailored risk transfer capabilities; and superior financial strength. To do so, we rely on a dynamic, culturally diverse group of employees, working in more than 100 countries, in a variety of challenging roles. As a Senior Machine Learning Engineer, you will be a key member of our Data Science team, focusing on translating business needs into actionable analytics and advanced AI solutions. This role offers the opportunity to innovate, explore, and build solutions for FM using emerging technologies.

Responsibilities

• Collaborate with Data Scientists, ML Ops Engineers, and Data Engineers to deliver statistical, AI, machine learning, and deep learning solutions to various business problems in property insurance.
• Develop and deploy machine learning and AI models on cloud platforms.
• Partner with ML Platform, Data Delivery, and Product teams to ensure smooth deployment and monitoring.
• Coach the team on MLOps best practices to ensure stability and scalability in ML projects.

Requirements

• Bachelor's degree in Data Science, Machine Learning, Computer Science, Software Engineering, Statistics, or a related field.
• 5+ years of post-graduate experience as a Data Scientist, Machine Learning Engineer, or Software Engineer.
• 3+ years of experience in end-to-end data science/ML product development.
• Experience with MLflow and ML platforms such as Databricks.
• Proficiency in Python or R.

Nice-to-haves

• Advanced degree in one of the fields listed above.
• 8+ years of experience in end-to-end data science/ML product development.
• 3+ years of experience leading data science/ML product development.
• Advanced knowledge and working experience in at least one of the following areas: Generalized Linear Models (Logistic Regression, Zero-Inflated Models, etc.), Model Regularization, Probability Distributions, Hypothesis Testing, Statistical Inference, Machine Learning (Random Forest, Clustering, Gradient Descent, Gradient Boosting, etc.), Simulation, Experiment Design, Non-Parametric Statistics.
• Experience in risk management and/or property insurance is strongly preferred.

Benefits

• Incentive plan
• Generous health and well-being programs
• 401(k) and pension plan
• Career development opportunities
• Tuition reimbursement
• Flexible work
• Paid time off allowances