Imran A.Private profile: Upwork shows its earnings only to signed-in members, so we check it every few weeks, not daily. MRR here is a rough estimate (Upwork's six-month earnings ÷ months active). Last read Nov 5, 2026.

Most financial models look convincing. Far fewer survive scrutiny from a board, a lender, or a regulator. I build the kind that do and I build the data systems and automation behind them. I’m a sitting Group CFO with dual chartered-accountant credentials (FCA — ICAEW & ICAP), plus CISA and CFE. The rare part: I’m equally at home in the model and in the data layer that feeds it Python automation, BI dashboards, ERP integrations, and scripted pipelines. I don’t just build the model, I audit it, and I engineer the data flow so the numbers are clean at the source. That combination — CFO judgment plus hands-on data engineering is hard to find in one person. Finance & modeling: • Financial modeling — 3-statement, DCF, M&A/merger, LBO, IPO, consolidation, sum-of-the-parts, budgeting, forecasting, option pricing. Built for decisions, not decoration. • FP&A & decision support — rolling forecasts, scenario/sensitivity analysis, unit economics, and board-level analysis that turns the model into a clear recommendation. • M&A due diligence & QoE — 30+ US financial due-diligence engagements; led cross-border pharma acquisition DD. • Feasibility — including a SAR 1B+ hospital feasibility alongside a Big-Four firm and an international clinical partner. Data, analytics & automation: • BI dashboards & analytics — Power BI (data models, 45+ DAX measures), Excel analytics, KPI dashboards that turn raw operational data into decisions. • Automation & pipelines — Python and Google Apps Script automation, scheduled reporting, API/ERP integrations (incl. Odoo via custom proxies), GitHub-based workflow automation. • Data engineering for finance — building the clean, reconciled data layer beneath financial reporting: extraction, transformation, validation, and delivery. How I work: I start from the decision the output has to support then build backward, whether it’s a model or a data pipeline. You get something transparent, fully traceable, and defensible line by line, plus a plain-English read of what the numbers mean and what they demand. No black boxes. No vanity metrics. No good-looking numbers that fall apart under a hard question. 20+ years across finance leadership, assurance, and analytics. If you need a model, a dashboard, or the data system behind them built to be staked on let’s talk.