Job at a glance
At MetLife, data isn’t just a tool – it is a catalyst for growth. As part of our Data & Analytics organization, you’ll unlock trusted insights that drive bold decisions, power personalized customer experiences, and deliver lasting business impact. We’re building the future of data – one that’s governed responsibly, engineered for scalability, and designed for growth. When you join us, you’re not just supporting the business – you’re empowering it.
Let’s transform insight into impact and data into action, together. The Opportunity The Data Scientist II is responsible for designing and implementing scalable data science, machine learning, Generative AI, and advanced analytics solutions that drive business value and informed decision-making. This role supports the full analytics lifecycle including data acquisition, SQL development, data preparation, feature engineering, model development, deployment, monitoring, and responsible AI practices.
The position contributes to production-ready solutions using modern AI technologies and responsible AI principles. Key Responsibilities Design, build, validate, deploy, monitor, and optimize analytics, machine learning, and AI solutions. Perform data extraction, SQL development, data preparation, exploratory analysis, feature engineering, and model evaluation. Develop production-grade predictive and Generative AI solutions using structured and unstructured data.
Support foundation model adaptation, prompt engineering, embeddings, vector databases, RAG-based AI applications, and agentic AI workflows. Utilize Databricks, Apache Spark, and cloud-based analytics environments where applicable. Generate actionable insights and communicate business impact to stakeholders. Monitor solution performance and drive continuous improvement. Leverage AI-augmented tools to enhance productivity while ensuring output quality.
Collaborate with Business, Technology, Operations, and D&A capabilities including Data Governance, Data Quality, Data Modeling, Data Architecture, Data Science, DevOps, and BI & Insights teams. Ensure adherence to quality, security, compliance, explainability, MLOps, model governance, and responsible AI standards. Required Qualifications Bachelor's degree in Mathematics, Statistics, Operations Research, Computer Science, Engineering, Social Sciences, or related quantitative field.
3-5 years of experience in data science, analytics, machine learning, or related quantitative disciplines. Hands-on experience with Python, SQL, statistics, hypothesis testing, feature engineering, and predictive modeling. Experience with one or more machine learning frameworks (Scikit-learn OR TensorFlow OR PyTorch). Experience with data preparation, data wrangling, analytics solution development, and stakeholder engagement.
Foundational knowledge of Generative AI including large language models, prompting, embeddings, vector stores, and RAG. Strong analytical, communication, and structured problem-solving skills. Preferred Qualifications Experience with Databricks, Apache Spark, or cloud analytics platforms. Experience with NLP technologies including spaCy, Transformers, OCR, or related tools. Knowledge of agentic AI architectures, multi-agent workflows, AI copilots, and AI-augmented development environments.
Exposure to model evaluation, benchmarking, monitoring, and MLOps fundamentals. Portfolio of academic, internship, personal, or professional data science projects. Location Expectation: This is a hybrid role r equiring a minimum of 3 days per week in office. The expected salary range for this position is $90,000 - $115,000 . This role may also be eligible for annual short-term incentive compensation.
All incentives and benefits are subject to the applicable plan terms. Benefits We Offer Our U.S. benefits address holistic well-being with programs for physical and mental health, financial wellness, and support for families. We offer a comprehensive health plan that includes medical/prescription drug and vi