AI, Business Analyst, Information Technology - New York

ilani•New York, NY

4d•$90,000 - $100,000

About The Position

We are passionate about our business and our culture, and are seeking individuals with that same drive. If you are passionate about shaping the future of technology and making a meaningful impact in financial services, we want to hear from you. Moelis is building an AI platform to equip our bankers and corporate functions with tools that unlock productivity and drive revenue growth. We are looking for an AI Business Analyst (Analyst level) who sits at the intersection of business strategy and technology execution. This is a great role for someone early in their career who enjoys solving ambiguous problems, working with data, and translating business needs into practical AI solutions. You’ll learn from experienced mentors, get exposure to senior stakeholders, and contribute to a multi-year AI roadmap for a global investment bank. Why this Role Exists The firm is evolving its AI strategy to deliver governed, banker-grade analytics and agentic capabilities across the front-, middle-, and back-office. To realize this vision, we need an analyst who can: Discover and prioritize high-value AI use cases Translate business workflows into clear requirements for data science and engineering teams Help measure impact, adoption, and risk of deployed solutions If you’re curious about how AI can transform investment banking and enjoy connecting people, processes, and data, we’d like to speak with you.

Requirements

Bachelor’s Degree required, with preferred emphasis in Information Systems, Data Science/Analytics, Computer Science, Finance, or related field.
1+ of experience as a Business Analyst, Data Analyst, or in a related technical or operations role.
Strong analytical and problem-solving abilities; able to turn data and qualitative input into clear insights and recommendations.
Excellent written and verbal communication skills; able to explain technical concepts in simple, business-friendly language.
Comfort working with data in Excel or similar tools to structure analyses and summarize findings.
Solid proficiency with Microsoft Office (Excel, PowerPoint, Word); experience building clear, executive-ready materials.
Familiarity with generative AI tools and large language models (e.g., ChatGPT, Copilot, Gemini) and an interest in how they can be applied to real business workflows.
Self-starter with a growth mindset, comfortable operating in a fast-paced, evolving environment with shifting priorities.
High attention to detail and strong organizational skills; able to manage multiple workstreams simultaneously.
Collaborative team player who builds strong relationships with stakeholders across technology and the business.
Curious, creative, and comfortable asking questions to deeply understand processes and requirements.

Nice To Haves

Experience within financial services or professional services is preferred but not required.
Basic familiarity with Python, SQL, or data analytics tools (e.g., Power BI, Tableau) is preferred; willingness to learn is essential.
Exposure to concepts such as prompt design, retrieval-augmented generation (RAG), or workflow automation platforms is a plus.

Responsibilities

Stakeholder Collaboration Partner with business stakeholders and IT teams to identify opportunities where AI can enhance decision-making, accuracy, and efficiency.
Act as a bridge between technical teams and business users, ensuring clear communication and alignment throughout projects.
Assist in preparing findings, documentation, and project updates.
Requirements Gathering & Execution Support the identification, documentation, and refinement of business requirements for AI-driven solutions.
Participate in workshops, interviews, and working sessions with bankers to understand their workflows, pain points, and information needs.
Translate business needs into actionable technical deliverables for engineering and data science teams.
Solution Design & Implementation Analyze existing business processes to identify bottlenecks, manual tasks, and automation opportunities.
Collaborate with data scientists and engineers to prototype, test, and iterate AI solutions (e.g., generative AI assistants, classification models, workflow automation).
Coordinate user acceptance testing (UAT), organize feedback sessions, and capture enhancement requests.
Support the creation of user guides, training materials, and demos to drive adoption.
Measure Impact, Risk, and Adoption Help define KPIs and success metrics for AI use cases (e.g., time savings, accuracy, revenue enablement, user satisfaction).
Support performance measurement and usage tracking for deployed AI solutions and summarize findings for stakeholders.
Assist with documentation related to data quality, model governance, and controls in partnership with risk, legal, and compliance teams.
Research and Stay Current on AI in Financial Services Research emerging AI technologies (especially generative AI and automation platforms) and assess their relevance to investment banking workflows.
Benchmark internal initiatives against external best practices and market trends in AI for financial services.