AI assisted Equity Research Automation

I need a Python developer to build a POC that automates the equity research workflow — extracting financial data from listed-company filings, populating a DCF valuation model in Excel, and generating a draft research report in Word — so a small analyst team can cover more companies. Equity Research Automation (POC, weeks 1–6) End-to-end pipeline that automates the manual parts of the equity research workflow so a small analyst team can scale coverage to more listed companies without adding headcount. Given a listed company's quarterly or annual financial filing PDF, the system: Extracts financial statements — income statement, balance sheet, and cash flow parsed into clean structured data, mapped to a standard chart of accounts. Populates the financial model — writes historical financials into a DCF-based three-statement Excel model with forecast structure (5–10 year horizon) and valuation outputs (free cash flow, WACC, terminal value, enterprise value, target price per share). Generates a draft research report — produces a Word document formatted in a standard equity research template: front page with recommendation, target price and upside; financial summary tables; valuation summary; key drivers and charts; placeholder sections for analyst commentary. The output is a near-publication-quality first draft. The analyst reviews, adjusts assumptions (WACC, growth rates, sector drivers), and finalizes the narrative sections with their judgment on the 12-month outlook and rating call.