26 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.
You’ll spend mornings pulling data from Excel, Power BI, or Google Sheets to update ESG scores and asset performance. Expect focused blocks for financial modeling—forecasting emissions or cash flows—in Excel and building visuals in PowerPoint or Power BI.
Afternoons often mean meetings: present findings to portfolio managers, meet company management for due diligence, and write client presentation slides. You’ll also follow up with backers and update QuickBooks or finance records for auditing and tax transparency.
Learn Microsoft Excel deeply: pivot tables, INDEX/MATCH, and basic VBA or macros. Excel is where you build models, run valuations, and prepare charts for technical reports.
Next, practice PowerPoint for client presentations and Power BI or Alteryx for automating dashboards and data prep. Know Outlook for scheduling and QuickBooks enough to verify finance records. Google Docs is fine for collaborative notes.
Yes, AI can help draft reports, summarize meetings, and suggest model structures, but never paste confidential spreadsheets into public AI tools. Treat client or deal data as private.
Use on-premise or approved enterprise AI (your firm’s Power BI/Alteryx integrations or secured models) and always validate AI outputs against your own financial models and source documents before advising clients.
Salaries vary widely by country and employer; in many firms pay is tied to level (analyst vs senior), asset class, and whether you handle transactions. Working on deal execution or raising debt often brings higher pay or bonuses.
Base salary is only part: bonuses from successful investments, client retention, or transaction fees matter. Larger asset managers or banks generally pay more than small advisory shops.
Start with Excel financial modeling courses (valuation, cash-flow forecasting) and an intro ESG course covering metrics like carbon intensity and governance scores. Use free datasets to practice building forecasts and dashboards in Power BI.
Work on real examples: create an ESG due-diligence slide deck in PowerPoint, run a simple securities valuation in Excel, and document your process in Google Docs. Try internships or volunteer to help a student fund with investment tracking.
Both build models, value securities, and prepare investor presentations. The difference is focus: ESG analysts add environmental, social, and governance metrics into valuations and advice—so you quantify emissions, supply-chain risks, and governance scores in Excel and Power BI.
You also meet different stakeholders: ESG analysts spend more time with sustainability teams and external auditors to maintain transparent operations for tax and compliance, not just portfolio managers.
Being able to translate ESG data into investment impact—i.e., build a clear Excel model that links emissions or governance improvements to cash-flow or valuation changes—sets you apart.
Equally important is communication: turn complex model outputs into concise PowerPoint slides and present findings clearly to portfolio managers and clients. That combination drives recommendations and wins trust.