AI Data Analyst, CAIS

• 2–4 years of experience in data analysis, data science, or related roles, preferably in the Technology or Financial Services industry
• Proficiency in SQL and at least one programming language (Python preferred) for analytics and machine learning
• Strong skills in data modeling, reporting, and visualization (e.g., Tableau, Power BI)
• Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and exposure to AI use cases such as NLP, generative AI, or recommendation systems
• Solid understanding of core machine learning algorithms (e.g., regression, classification, clustering) and their practical application to business use cases
• Ability to understand complex problems, design structured solutions, and communicate insights clearly to stakeholders
• Strong communication and collaboration skills with the ability to bridge technical and business perspectives

Desirable

• We are seeking a full-time AI Data Analyst Associate to join our Data Team
• This hybrid role blends data analysis, reporting, and modeling with applied data science and AI techniques
• The individual will partner with colleagues across Marketing, Sales, Product, Operations, and other teams to enable data-driven decision-making through analytics, machine learning, and AI-powered insights
• As CAIS continues to expand its AI-first strategy, this role will help explore and implement AI-driven solutions that improve efficiency, uncover opportunities, and accelerate innovation across the organization
• Become an expert in Alternative Investments and CAIS data, leveraging this expertise to deliver actionable insights that drive business outcomes
• Apply machine learning and AI techniques (e.g., predictive modeling, NLP, recommendation systems, generative AI) to solve business problems and improve decision-making
• Collaborate with Product and Engineering teams to support product launches, data migrations, monitoring, and reporting with an emphasis on AI-enhanced automation and analytics
• Partner with teams to develop and maintain business intelligence dashboards, advanced analytics, and AI-driven reporting solutions
• Contribute to data governance and cataloging efforts, ensuring data assets are well-documented, governed, and ready for AI-driven use cases
• Build and maintain scalable data models that support both operational reporting and strategic AI initiatives
• Experiment with emerging AI technologies and tools to enhance workflows and deliver proof-of-concepts for business stakeholders
• Share knowledge and promote adoption of AI-powered practices by creating reusable documentation, training, and stakeholder resources