Finance-Asset Management

Finance-Asset Management

VM

• New York, New York (Remote) Hi Everyone, Hope you are doing well. We at Datamundi are looking for Sector Evals- Finance Asset Management Experts. Please find the below job description. Responsibilities As a Finance Domain Expert, you will be responsible for the following key tasks: Workflow Definition: Collaborate with our AI and engineering teams to define the most common research-based workflows within your specific domain (e.g., M&A deal analysis in Investment Banking, company valuation in Equity Research, portfolio construction in Asset Management). Evaluation Creation: Develop and create comprehensive evaluations and test cases to assess the completion of these defined workflows. This involves specifying inputs, expected outputs, and the criteria for success. Capability Assessment: Design evaluations to assess the key capabilities of the LLM in handling complex financial tasks, including data extraction, financial statement analysis, market trend identification, and risk assessment. Data Curation & Annotation: Provide guidance on identifying and curating high-quality financial data and content that is essential for training and fine-tuning the LLM. Feedback & Iteration: Work closely with the product team to provide constructive feedback on the LLM's performance and suggest improvements to enhance its accuracy and relevance. Key Requirements Domain Expertise: 12+ years of practical, professional experience in one of the following fields: Investment Banking: Experience with M&A, capital markets, or corporate finance. Private Equity: Experience with deal sourcing, due diligence, and portfolio management. Asset Management: Experience with portfolio management, investment strategy, or quantitative analysis. Equity Research: Experience with company analysis, financial modeling, and report writing. Experience : Entry level, Mid level and Executive level professionals Analytical Skills: Strong analytical and critical thinking abilities to break down complex financial processes into logical, measurable steps. Communication: Excellent communication skills and the ability to articulate complex financial concepts to a non-finance audience. Technical Acumen : A basic understanding of AI, machine learning, or experience working with technical teams is a significant plus. Attention to Detail: Meticulous attention to detail is crucial for creating accurate and robust evaluation criteria. Private Equity | Market & Commercial Diligence Definition: Deep-dive workflows that size a target’s market, analyze competitive dynamics, test growth drivers, and capture customer / channel insights to support—or challenge—an investment thesis.

Data input types: Public filings (10-K/annual reports), industry research databases (PitchBook, CapIQ, Gartner, IB reports), consultant decks, company websites & investor presentations, expert-network call notes/transcripts, press releases, government statistics (e.g., Census, BLS). Asset Management | Earnings Analysis & Quarter Updates Definition: Fast-turn workflows that digest a company’s quarterly results, benchmark them against expectations, and refresh internal views or models ahead of—or immediately after—an earnings event.

Data input types: Company earnings release, slide deck, SEC 10-Q/8-K, earnings-call transcript, sell-side consensus, management follow-up notes, and models. Investment Banking | Market & Competitive Research Definition: Sector-intelligence workflows that size an industry, map competitors, highlight secular trends, and position a client (or target) within that landscape so bankers can craft compelling pitches, valuations, and strategic recommendations.

Data input types: Public filings & earnings call transcripts (10-K/10-Q/20-F, S-1), industry and equity-research reports, company websites & investor presentations, product review sites, press releases and trade-press coverage, government statistics (Census, BLS), social-