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Top Hybrid Machine Learning Jobs in New York City, NY
As a Lead Machine Learning Engineer, you will design and implement machine learning solutions, collaborate with product and engineering teams, and oversee project execution. Your role includes writing code, setting project milestones, conducting code reviews, coaching team members, and ensuring best practices for service maintenance and deployment.
As an Applied AI/ML Data Scientist, you will innovate investment banking through AI and data analytics, develop machine learning systems, analyze complex datasets, and present insights to stakeholders. You'll collaborate with a diverse team to push the boundaries of financial technology.
The Principal Data Scientist will lead the development of machine learning models to enhance customer experiences and anticipate needs across Capital One's digital products. Responsibilities include data exploration, model building, and collaboration with business teams to improve outcomes in marketing and fraud prevention.
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As a Data Analytics Senior Consultant at CNA, you will lead data analytics initiatives to optimize underwriting strategies. Responsibilities include developing automated scorecards, conducting scenario analyses, providing insights for decision-making, and collaborating with senior leadership and cross-functional teams to drive business outcomes.
The Senior Software Engineer in Machine Learning is responsible for architecting and scaling personalization and search platforms for the Max streaming app. The role involves collaborating with data scientists, contributing to machine learning systems, optimizing code, and advocating for customer-focused innovation.
As an Applied AI Scientist at ZS, you will develop advanced algorithms, execute statistical techniques on large data sets, evaluate new datasets, and contribute to thought leadership in AI topics.
The Senior Machine Learning Engineer will create end-to-end AI and machine learning solutions, collaborating with stakeholders to define project requirements, gather data, and deploy models into production. Responsibilities include analyzing data for insights, managing projects from start to finish, and staying updated on industry trends to drive innovation.
The Machine Learning Engineer will build and deploy models to assess risks in the payments domain, collaborate across teams, develop scalable frameworks for analysis, and communicate findings to stakeholders. The role requires deep knowledge in machine learning, statistical techniques, and programming.
The Machine Learning Infra Engineer will bridge the gap between data science and production systems by optimizing models for runtime performance, designing scalable MLOps pipelines, and implementing monitoring frameworks. They will work closely with data scientists to improve workflows and ensure reliability across the system, while also developing data versioning and deployment strategies.
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The Senior Machine Learning Engineer will develop and optimize NLP algorithms, train large language models, collaborate with cross-functional teams, and mentor junior engineers, all while advancing the company's technology stack and delivering new features rapidly.
Top hybrid Companies in New York City, NY Hiring Data + Analytics Roles
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