Top Hybrid Data & Analytics Jobs in New York City, NY
The Principal for Alternative Data Products at TransUnion is responsible for driving the strategy and development of products utilizing alternative data for underwriting and risk assessment. This role involves sourcing diverse data, managing product roadmaps, ensuring compliance with data regulations, and leading cross-functional teams to innovate and scale products globally.
The Analyst role in Consulting Services focuses on client engagement for Marketing Solutions, leveraging analytics and quantitative analysis to provide insights. Responsibilities include conducting data investigations, visualizing findings, and helping clients understand data relations to business objectives.
The Business Management Analyst will support JPMC's Acquisitions & Strategic Investments team by conducting financial analyses, preparing management reports, managing portfolio presentations, and identifying automation opportunities. Key responsibilities include coordinating with various stakeholders and assisting with controls and tracking processes.
The Outsourced Chief Investment Office Analyst will support clients by understanding investment plans and working with Senior Portfolio Managers on investment reviews and tactical asset allocations. Responsibilities include business development support, relationship management, and learning the investment platform. Strong analytical skills and the ability to work with cross-functional teams are essential.
The Collateral Eligibility Business Architect VP will drive governance and business integration of J.P. Morgan’s Collateral Eligibility Service, focusing on data management, process improvement, and innovation in collateral efficiency for liquidity and transaction management.
The Senior Business Analyst at Capital One Shopping is responsible for analyzing business challenges, performing product modeling, supporting marketing efforts, and enhancing credit risk strategies. The role requires collaboration across various teams to implement improvements and drive business growth through strategic and analytical insights.
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The AI Model Risk position at MetLife involves managing risks related to Artificial Intelligence and Machine Learning models. Responsibilities include challenging modeling decisions, assessing risks, collaborating with internal teams and vendors, and ensuring mathematical and conceptual soundness of models. Required skills include experience in statistical, ML or AI model development, programming skills in Python, R, and/or C#, and the ability to work collaboratively. A graduate degree in a quantitative field and 3+ years of experience are also required.
As a Senior Data Scientist, you will lead analytics projects, analyze user behavior, develop KPIs, conduct A/B testing, implement statistical models and machine learning algorithms, and collaborate with cross-functional teams to drive business impact and growth.
The People Analytics Analyst will enhance data-informed decision-making regarding workforce and business strategies, focusing on analytical reporting and the use of an HRIS system to improve People Analytics processes and communications within the organization.
The Principal Data Scientist is responsible for building data acquisition pipelines, utilizing various R frameworks for data processing and analysis, implementing data preprocessing techniques, executing machine learning models, generating visualizations, and deploying scalable models within the company’s infrastructure.
As a Senior Research Scientist at Kensho, you will develop innovative solutions in Machine Learning and NLP, focusing on complex tasks like long-context QA and document extraction. Collaborate with a team to enhance existing models, create evaluation benchmarks, and engage in academic partnerships, all while utilizing advanced computational resources.
The Director of People Analytics will lead a team to transform data into insights that enhance business strategies. Responsibilities include integrating analytics into operations, mentoring analysts, and collaborating with executives on data-driven decision-making regarding employee lifecycle metrics and organizational health.
The Sr. Data Engineer will design and build scalable data pipelines across various sources to support data-driven decisions and generative AI initiatives. Responsibilities include collaborating with cross-functional teams, implementing data engineering principles, and optimizing performance and security of data applications.
Top hybrid Companies in New York City, NY Hiring Data + Analytics Roles
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