Lead Quantitative Analytics Consultant

Description

Summary: The Lead Quantitative Analytics Consultant drives advanced analytics and data-driven decision making across MetLife's U.S. Group Disability business, shaping how analytics, predictive modeling, and AI are used to improve business outcomes. Highlights: 1. Shape how analytics, predictive modeling, and AI improve business outcomes 2. Partner with leaders across various departments to solve complex challenges 3. Opportunity to build new ways of working and influence future analytics **The Opportunity** The **Lead Quantitative Analytics Consultant**is responsible for driving advanced analytics and data\-driven decision making across MetLife’s U.S. Group Disability business. Guided by our purpose – *always with you, building a more confident future* – and our New Frontier strategy focused on stronger growth, attractive returns, and all\-weather performance, this is an exciting opportunity to help shape how analytics, predictive modeling, and AI are used to improve business outcomes. This role sits at the intersection of business strategy, analytics, and innovation. You will partner with leaders across Pricing, Finance, Operations, Product, and Underwriting to solve complex business challenges, uncover actionable insights, and develop analytical frameworks that support critical decisions. Success in this role requires curiosity, strong quantitative thinking, and the ability to thrive in an environment where not every solution is predefined. You will have the opportunity to help build new ways of working while influencing the future direction of analytics within the Disability business. **Key Responsibilities** * Lead advanced analytics initiatives supporting Disability pricing, business performance, projections, and operational effectiveness. * Create predictive models, statistical analyses, and analytical frameworks to improve business outcomes and decision\-making. * Design and execute treatment/control and quasi\-experimental analyses to measure the impact of business initiatives. * Manage cost\-benefit analyses, forecasting exercises, and business case assessments that support strategic priorities. * Develop early warning indicators, performance monitoring approaches, and driver analyses to identify emerging trends and opportunities. * Oversee model governance, validation standards, and analytical best practices to ensure quality, reliability, and business relevance. * Coordinate with business stakeholders and reporting teams to deliver scalable analytics solutions, dashboards, and actionable insights. * Support ongoing model maintenance, refreshes, monitoring, and reporting activities while continuously identifying opportunities for enhancement and innovation. **Required Qualifications** * Bachelor’s degree in Data Science, Statistics, Mathematics, Economics, Actuarial Science, or a related quantitative discipline. * Strong analytical and quantitative problem\-solving skills with the ability to work effectively with large and complex datasets. * Advanced proficiency in Excel and experience using analytical programming languages such as Python, R, or SQL. * Experience applying statistical methods, predictive analytics, machine learning, or quantitative modeling techniques to business problems. * Ability to translate complex analytical findings into clear recommendations for technical and non\-technical audiences. * Strong communication, collaboration, and stakeholder management skills. * Associate of the Society of Actuaries (ASA) designation with progress toward Fellowship, or equivalent advanced quantitative experience. **Preferred Qualifications** * 5\+ years of experience in data science, quantitative analytics, actuarial science, predictive modeling, or a related field. * Experience within insurance, employee benefits, financial services, or other data\-intensive industries. * Experience using Alteryx to prepare, transform, and analyze data. * Familiarity with Power BI or similar visualization tools to build, maintain, and enhance reporting solutions. * Experience with cloud\-based data environments, Databricks, or large\-scale data platforms. * Knowledge of predictive modeling techniques such as GLMs, classification models, segmentation, or time series analysis. * Experience supporting model governance, validation, or regulatory compliance initiatives. * Ability to navigate ambiguity, challenge existing approaches, and develop innovative analytical solutions to complex business problems.