Top Data Science Jobs in New York City, NY
The Senior Data Scientist, Data Products role involves leveraging data to enhance product creation and strategy through collaboration, automated systems, quality metrics, and ad-hoc analysis. Responsibilities include creating insights and applying the latest technology trends while leading projects independently.
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As a Senior Data Scientist at Pie, you will develop best-in-class AI/ML solutions for commercial insurance, focusing on pricing, underwriting, and claims models. Collaborating with multiple teams, you'll enhance data-driven decision-making, conduct model diagnostics, and support deployment and automation of scalable ML pipelines that meet real business challenges.
As a Senior Revenue Operations Analyst, you will oversee sales process planning and optimization, ensuring data accuracy in Salesforce and improving revenue operations. Key responsibilities include opportunity management, data analysis, and reporting, collaborating with sales and IT teams to enhance processes and outcomes.
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As a Research Scientist on the Interpretability team, you will develop methods for understanding large language models through the reverse engineering of algorithms within neural networks. This involves designing and conducting robust experiments to achieve mechanistic interpretability, aimed at improving the safety and performance of AI systems.
The role involves driving the data science and analytics initiatives by partnering with go-to-market leaders to define KPIs, analyze customer behavior, and build a data-driven culture in a rapidly growing AI organization.
As a member of the Data Science and Analytics team, you'll analyze user behavior data, define product success metrics, identify product improvement opportunities, and build a data-driven culture to inform product strategy and commercial growth.
As an AI for Code Research Scientist, you will improve models and research for real-world problems by prototyping concepts and running experiments, collaborating with a team to drive foundational research direction.
As a Staff Data Scientist at Curinos, you will leverage machine learning and data science to enhance banking customer engagement and optimize marketing strategies. You'll work with cross-functional teams to develop algorithms, improve models, and implement best practices, influencing the direction of data-driven decision-making within the company.
The Staff Data Scientist for Brokerage at Robinhood will develop and implement sophisticated data models for analyzing market structures and optimizing order routing. This role involves collaborating with trading teams, conducting post-trade analysis, and translating business needs into data-driven solutions while utilizing statistical modeling and game theory.
As an A&R Data Specialist at AWAL, you will drive data optimization strategy, monitor music performance, generate reports, and work with analytics to improve artist engagement and identify new opportunities. Your role involves researching music trends and collaborating on audience growth insights.
Growth Data Scientist role at Quizlet focusing on driving business insights through data, developing analytical frameworks, and working closely with Product, Engineering, and Design teams to drive user growth. Responsible for A/B testing, analyzing user behavior, and informing product roadmap and strategy using data science techniques.
Sr. Data Scientist, Analytics - Ads role at Quizlet, working on building an amazing ads product for users and advertisers by leveraging insights from ads and user engagement data. Responsible for A/B testing, presenting insights, informing product roadmap, and collaborating with cross-functional teams.
The Credit Analyst will perform fundamental credit research to identify investment opportunities in the High Yield market. Responsibilities include analyzing capital structures, developing trade ideas, monitoring positions, and maintaining external relationships to form issuer views.
As a Data Scientist, you will identify new data sets, engage with vendors, build tools for data ingestion, analyze datasets, research alpha signals, monitor data collection, and enhance data management technologies.
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