[Remote] Senior Data Scientist

Note: The job is a remote job and is open to candidates in USA. Reinsurance Group of America, Incorporated is a Fortune 200 Company focused on life- and health-related solutions. The Senior Data Scientist will pioneer advanced machine learning and generative AI solutions, architecting and implementing analytical models to address business challenges while mentoring emerging talent and collaborating with stakeholders.ResponsibilitiesEnd-to-End Modeling: Design, develop, and deploy sophisticated machine learning models that address mission-critical business challenges, including underwriting automation, pricing optimization, and claims analytics. This includes collaborating with business stakeholders to define requirements, selecting appropriate algorithms, engineering features, tuning model parameters, and integrating solutions into production environments for seamless business adoptionGenAI Solution Development: Lead the end-to-end development and implementation of generative AI solutions, leveraging large language models (LLMs) for advanced document processing, automated content creation, and streamlining repetitive business processes. Responsibilities include identifying high-value GenAI use cases, fine-tuning models for domain-specific tasks, and ensuring responsible AI practices such as bias mitigation and transparencyTechnical Leadership: Serve as a technical authority and mentor for colleagues, providing expert guidance on best practices in machine learning modeling, code development, and solution architecture. This involves conducting code reviews, sharing knowledge of emerging technologies, and fostering a culture of technical excellence within the data science teamProject Leadership: Lead and manage small-scale projects, including defining scope and objectives, developing project plans, allocating resources, and coordinating activities across cross-functional teams. Maintain proactive communication with stakeholders to track progress, address risks, and ensure timely and successful project delivery aligned with business goalsData Pipeline Architecture: Architect, develop, and maintain robust, automated data pipelines and ETL processes in partnership with data engineering teams. This includes designing scalable workflows for data ingestion, transformation, and validation, ensuring data quality and availability for analytics and modeling, and optimizing pipeline efficiency for large, complex datasetsStakeholder Communication: Effectively communicate complex analytical findings, model insights, and actionable recommendations to a wide range of stakeholders—including business leaders and senior management—using clear visualizations and storytelling. Facilitate data-driven decision-making by translating technical results into business value and strategic impactModel Governance: Champion and enforce rigorous model governance practices by conducting thorough model validation, ongoing monitoring, and comprehensive documentation. Ensure all models adhere to standards for accuracy, fairness, and reproducibility, and proactively address issues related to model drift, regulatory compliance, and ethical considerations in AI deploymentSkillsBachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field; OR a Bachelor's degree with equivalent experience5-7 years of progressive experience in data science and machine learningDemonstrates a deep understanding of advanced statistical techniques, such as regression analysis, hypothesis testing, time series analysis, and multivariate statisticsApplies a broad range of machine learning algorithms—from supervised and unsupervised learning to ensemble methods and deep learning—to extract meaningful insights and drive data-driven decision-making across complex business challengesPossesses advanced proficiency in Python and/or R, leveraging these languages for data manipulation, statistical modeling, and deployment of machine learning solutionsSkilled in using modern ML and GenAI frameworks, such as scikit-learn for traditional models, TensorFlow and PyTorch for deep learning, and LangChain, Langgraph, openai, crewai, dspy, mlflow, etc., for building, orchestrating and evaluating generative AI applicationsExperience includes developing and optimizing code, managing dependencies, and applying best practices in version control and containerizationHands-on experience implementing GenAI technologies, including large language models (LLMs) for natural language processing and understandingProficient in prompt engineering to fine-tune model outputs, utilizing retrieval-augmented generation (RAG) strategies to enhance responses with relevant knowledge, and integrating APIs to embed GenAI capabilities into production workflows and business applicationsExpertise in using SQL for querying, transforming, and aggregating data from relational databasesDemonstrates experience working with both structured data (e.g., tables, spreadsheets) and unstructured sources (e.g., text, images, documents), applying appropriate preprocessing and feature engineering techniques to ensure data quality and relevance for analytics and modelingExhibits excellent problem-solving skills, approaching challenges creatively and analyticallyCapable of dissecting complex issues, identifying root causes, and designing innovative solutionsFrequently takes a fresh perspective on existing processes or models, independently developing and implementing strategies that improve efficiency, accuracy, or business valueEffectively communicates difficult or sensitive information to diverse stakeholders, translating complex technical concepts into clear, actionable insights for both technical and non-technical audiencesSkilled at facilitating discussions, presenting findings, and building consensus among cross-functional teams to drive project alignment and successful outcomesServes as a force multiplier for the team by mentoring junior members, providing guidance on technical challenges, and sharing best practices in data scienceActively contributes to team knowledge-sharing, fostering a collaborative and growth-oriented environment that enhances overall team capability and performanceDemonstrates a strong understanding of key business drivers, market dynamics, and organizational prioritiesApplies data science expertise to identify opportunities for improvement, solve high-impact business problems, and deliver actionable insights that support strategic decision-making and value creation for the companyPh.D. in a related quantitative fieldExperience in the life/health insurance or reinsurance industryExperience working with Databricks, Snowflake, and AWS tech stacksExperience working with large longitudinal datasets using actuarial methods of analysisBenefitsAn annual bonus plan that includes all rolesSome positions are eligible for participation in our long-term equity incentive planA full range of health, retirement, and other employee benefitsCompany OverviewReinsurance Group of America, Incorporated (NYSE: RGA) is a global industry leader specializing in life and health reinsurance and financial solutions that help clients effectively manage risk and optimize capital. It was founded in 1973, and is headquartered in Chesterfield, Missouri, USA, with a workforce of 1001-5000 employees. Its website is http://www.rgare.com.Company H1B SponsorshipReinsurance Group of America, Incorporated has a track record of offering H1B sponsorships, with 10 in 2026, 43 in 2025, 45 in 2024, 40 in 2023, 34 in 2022, 34 in 2021, 26 in 2020. Please note that this does not guarantee sponsorship for this specific role.