About the company
CAIS is the pioneer in democratizing access to and education about alternative investments and structured investment solutions for independent financial advisors, empowering them to engage and transact with leading asset managers on a massive scale through a wide variety of alternative investment products and technology solutions. CAIS provides financial advisors with access to a broad range of alternative investment strategies, including structured investments, hedge funds, private equity, private credit, real estate, and digital assets. CAIS also delivers industry-leading technology, operational efficiency, and world-class client service throughout the pre-trade, trade, and post-trade experience. CAIS supports over 50,000 advisors who oversee more than $6 trillion in network assets.
Job Summary
Responsibilities:
šBecome an expert in Alternative Investments and CAIS data, leveraging this expertise to deliver actionable insights that drive business outcomes. šApply machine learning and AI techniques (e.g., predictive modeling, NLP, recommendation systems, generative AI) to solve business problems and improve decision-making. šCollaborate with Product and Engineering teams to support product launches, data migrations, monitoring, and reporting with an emphasis on AI-enhanced automation and analytics. šPartner with teams to develop and maintain business intelligence dashboards, advanced analytics, and AI-driven reporting solutions. šContribute to data governance and cataloging efforts, ensuring data assets are well-documented, governed, and ready for AI-driven use cases. šBuild and maintain scalable data models that support both operational reporting and strategic AI initiatives. šExperiment with emerging AI technologies and tools to enhance workflows and deliver proof-of-concepts for business stakeholders. šShare knowledge and promote adoption of AI-powered practices by creating reusable documentation, training, and stakeholder resources.
Requirements:
š2ā4 years of experience in data analysis, data science, or related roles, preferably in the Technology or Financial Services industry. šProficiency in SQL and at least one programming language (Python preferred) for analytics and machine learning. šStrong skills in data modeling, reporting, and visualization (e.g., Tableau, Power BI). šFamiliarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and exposure to AI use cases such as NLP, generative AI, or recommendation systems. šSolid understanding of core machine learning algorithms (e.g., regression, classification, clustering) and their practical application to business use cases. šAbility to understand complex problems, design structured solutions, and communicate insights clearly to stakeholders. šStrong communication and collaboration skills with the ability to bridge technical and business perspectives.
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