> Markdown version of [/jobs/ext/3034280-data-scientist-ii](https://www.wearedevelopers.com/jobs/ext/3034280-data-scientist-ii). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist II - **Company:** MetLife - **Location:** New York, NY, United States (Remote available) - **Experience:** Experienced - **Salary:** $90,000.0 - $115,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Optical Character Recognition (OCR), Cloud Computing, Data Architecture, Data Cleansing, Data Governance, Data Mining, Database Development, DevOps, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Unstructured Data, Data Processing, Feature Engineering, Pytorch, Large Language Models, Multi-Agent Systems, Prompt Engineering, Apache Spark, Model Validation, Generative AI, Scikit Learn, Information Technology, Data Analytics, Machine Learning Operations, Virtual Agents, Spacy, Databricks - **Published:** September 23, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pm2wttxz4h ## About the Role * 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 requiring a minimum of 3 days per week in office. ## Description 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., * 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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