Top 12 Equity Analyst Skills to Put on Your Resume

In the competitive field of equity analysis, the right blend of technical depth, sharp judgment, and clean execution can tilt the odds in your favor. Below, you’ll find the 12 skills hiring managers expect to see, with practical ways to sharpen each one and present them convincingly on your resume.

Equity Analyst Skills

1. Financial Modeling
2. Excel
3. Bloomberg Terminal
4. SQL
5. Python
6. Valuation Techniques
7. Risk Management
8. SAS
9. Tableau
10. Equity Research
11. Portfolio Management
12. MATLAB

1. Financial Modeling

Financial modeling frames a company’s future in numbers. You translate strategy, market conditions, and unit economics into structured forecasts across the income statement, balance sheet, and cash flow, then test scenarios to gauge what really drives valuation.

Why It's Important

It’s the spine of equity analysis. Models connect raw data to decisions—valuation, sensitivity to assumptions, and risk all show up here.

How to Improve Financial Modeling Skills

Refine speed, structure, and skepticism. A few high-impact moves:

1. Master Excel: Get fluent with formulas, dynamic ranges, and model hygiene. Precision beats flair; consistency beats shortcuts.

2. Know the statements cold: Tie IS, BS, and CF with airtight links. Track drivers, not noise. Rebuild statements from 10-Ks to internalize mechanics.

3. Deepen valuation tools: DCF, trading comps, transaction comps—use each where it fits. Aswath Damodaran’s work is a sturdy compass.

4. Build from scratch: Templates hide cracks. Blank-sheet builds reveal logic, assumptions, and errors fast.

5. Stress test: Scenarios, sensitivities, and ranges. Show what breaks and where margins of safety live.

6. Seek feedback: Peer reviews catch unrealistic drivers, circularities, and brittle logic.

7. Keep current: Accounting updates, sector shifts, cost of capital dynamics—roll them into your assumptions.

Do this repeatedly. Clean structure, clear drivers, crisp outputs.

How to Display Financial Modeling Skills on Your Resume

2. Excel

Excel is the analyst’s workshop. You build models, audit data, and tell stories with numbers—all faster when the sheet obeys your hands.

Why It's Important

Speed and accuracy. From reconciliation to valuation, Excel is where analysis actually happens.

How to Improve Excel Skills

1. Functions that matter: XLOOKUP, INDEX/MATCH, SUMIFS, OFFSET, XMATCH, dynamic arrays. Kill the VLOOKUP crutch.

2. Pivot everything: PivotTables and PivotCharts for swift slicing, segmenting, and QA.

3. Model discipline: Inputs, calc, outputs—segregate. Consistent naming. Color conventions. Version control.

4. VBA and macros: Automate repetitive pulls and formatting. Small scripts, big time-savings.

5. Shortcuts: Keyboard-only modeling. Seconds saved compound across a quarter.

6. Add-ins: Bloomberg Excel Tools, Capital IQ plug-ins, and auditing tools when available.

Fast, auditable, and stable—those are the goals.

How to Display Excel Skills on Your Resume

3. Bloomberg Terminal

Live markets, deep company data, analytics, and messaging—without leaving the screen. For equity work, it’s a power grid.

Why It's Important

You get verified data, fast context, and tools for screening, charting, and comps—critical when the clock is grinding.

How to Improve Bloomberg Terminal Skills

1. Customize for flow: Pin workflows around DES, FA, WEI, EQS, GP, and EV. Build monitor views that mirror your coverage.

2. Learn the keys: Function keys, command shortcuts, and mnemonic chains. F8 Equity, then drill with muscle memory.

3. Excel Add-In: Pipe live fields into models with controlled refresh and tickers mapped cleanly.

4. APIs: For teams with engineering support, wire up batch pulls and bespoke dashboards.

5. Training and BMC: System tutorials plus Bloomberg Market Concepts sharpen both speed and interpretation.

6. Network: IB and MSG for channel checks, views, and quick clarifications across the street.

How to Display Bloomberg Terminal Skills on Your Resume

4. SQL

SQL pulls the truth out of relational data. Clean queries, clean joins, clean insights—no waiting on someone else’s export.

Why It's Important

Company data, market datasets, vendor tables—when you can query them directly, your analysis gets faster and more reliable.

How to Improve SQL Skills

1. Schema sense: Understand normalization, keys, and indexes. Design-aware analysts write queries that fly.

2. Core queries: SELECT, JOINs, GROUP BY, HAVING, subqueries. Nail the fundamentals.

3. Advanced tools: Window functions, CTEs, pivoting, conditional aggregation. Complex analysis, readable code.

4. Performance tuning: Index usage, EXPLAIN plans, avoiding scans. Faster results, fewer timeouts.

5. Practice on real data: Use public market or financial datasets; replicate recurring firm-level analyses.

6. Version and review: Store queries, document assumptions, peer review for logic leaks.

How to Display SQL Skills on Your Resume

5. Python

Python turns heavy lifting into routine work: data wrangling, time series, factor testing, scraping, risk models, report generation.

Why It's Important

Scale and repeatability. Build once, run often, adapt quickly when the market shifts.

How to Improve Python Skills

1. Core language: Clean syntax, functions, modules, virtual environments. Readability first.

2. Data stack: Pandas, NumPy, Polars for fast manipulation. Matplotlib/Seaborn/Plotly for visuals that explain themselves.

3. Finance libraries: yfinance or vendor APIs for data; statsmodels and scikit-learn for forecasting and factor work; QuantLib for pricing.

4. Automation: Scheduled data pulls, email reports, and dashboards. Turn ad hoc into daily cadence.

5. Projects: Build a valuation engine, a factor backtest, or an earnings-surprise monitor. Ship something.

6. Community: Ask, search, and share in places like Stack Overflow and r/Python. You’ll learn faster.

How to Display Python Skills on Your Resume

6. Valuation Techniques

Valuation is a toolkit—DCF for cash-driven clarity, trading comps for market context, transaction comps for control premia and precedent behavior. Use the right wrench.

Why It's Important

It anchors recommendations. Fair value isn’t a guess; it’s a reasoned range supported by drivers, risk, and evidence.

How to Improve Valuation Techniques Skills

1. Strengthen accounting fluency: Revenue recognition, leases, capitalized R&D, SBC—adjustments matter.

2. Calibrate WACC and growth: Market-implied risk premiums, realistic terminal assumptions, cross-checks with unit economics.

3. Segment analysis: Value segments separately when growth, margins, or risk diverge.

4. Cross-validate: Triangulate DCF with multiples and unit-based models. Convergence builds confidence.

5. Scenario thinking: Bull/base/bear with explicit drivers. Show what moves the needle.

6. Bias checks: Pre-mortems and blind checks to reduce anchoring and confirmation drift.

How to Display Valuation Techniques Skills on Your Resume

7. Risk Management

See the downside before it sees you. Identify, measure, and mitigate exposures at position and portfolio levels.

Why It's Important

Protect capital. Smooth drawdowns. Keep conviction grounded when volatility bites.

How to Improve Risk Management Skills

1. Define exposures: Factor, sector, style, liquidity, and single-name risk. Know your betas and your bet-themes.

2. Quantify: VaR/CVaR, drawdown stats, stress tests, and scenario shocks tied to real catalysts.

3. Diversify with intent: True diversification, not cosmetic. Correlation structures change—monitor them.

4. Position sizing and limits: Pre-commit rules for adds, trims, and exits. Stop-losses where appropriate, but rationale-driven.

5. Rebalance with discipline: Drift happens. Reset weights to risk budget, not just convenience.

6. Governance: Document assumptions, review exceptions, and keep a post-mortem cadence.

How to Display Risk Management Skills on Your Resume

8. SAS

SAS brings sturdy data handling and statistical muscle, especially for large structured datasets and time-series modeling used in forecasting and attribution.

Why It's Important

For teams embedded in SAS environments, it streamlines ingestion, transformation, and analysis with auditability.

How to Improve SAS Skills

1. Core programming: Data step, PROC SQL, macros. Clean logs, clear libraries, reproducible workflows.

2. Statistical procedures: PROC MEANS, FREQ, REG, ARIMA/ETS for forecasting and signal extraction.

3. Performance: Indexing, formats, and efficient joins to tame large tables.

4. Interop: Smooth handoffs to Excel, CSV, or Python/R when needed.

5. Practice on market data: Build pipelines for prices, fundamentals, and calendars. Schedule and monitor runs.

6. Documentation: Comment code, version control, and error handling—especially for production jobs.

How to Display SAS Skills on Your Resume

9. Tableau

Tableau turns dense data into visuals you can navigate—fast. Great for dashboards, board-ready exhibits, and quick pattern-spotting.

Why It's Important

Clear visuals change minds. Good dashboards surface drivers and outliers without a wall of text.

How to Improve Tableau Skills

1. Prep first: Clean data before viz. Consistent dimensions, clear granularity, tidy joins.

2. Advanced charts: Waterfalls, small multiples, candlesticks, cohort views—choose form to match the question.

3. Calculated fields: Ratios, rolling metrics, YoY/QoQ, and custom KPIs aligned to your thesis.

4. Interactivity: Filters, parameters, and actions that support drill-downs without confusion.

5. Performance: Extracts, index-aware queries, and minimal overly-dense worksheets.

6. Learn by copying: Rebuild strong public dashboards to internalize structure and flow.

How to Display Tableau Skills on Your Resume

10. Equity Research

Research blends numbers with narrative. You dissect industries, competitors, and management choices to forecast, value, and recommend.

Why It's Important

Great research shapes conviction and timing. It also survives scrutiny from PMs, clients, and risk committees.

How to Improve Equity Research Skills

1. Stay current: Earnings calls, filings, channel checks, and macro cues. Build a daily cadence that sticks.

2. Model-meets-memo: Align your thesis, catalysts, and risks with the model’s actual drivers.

3. Sharpen writing: Clear headers, crisp takeaways, and visuals that do the talking. No fluff.

4. Benchmark relentlessly: Peers, substitutes, and value chains. Edge often hides in relative positioning.

5. Seek feedback: PM pushback, peer reviews, and post-catalyst autopsies to hone judgment.

6. Ethics and compliance: Tight process, documented sources, and clean walls—non-negotiable.

How to Display Equity Research Skills on Your Resume

11. Portfolio Management

Turn ideas into positions, positions into a portfolio, and a portfolio into risk-adjusted returns that hold up.

Why It's Important

Great calls can still lose money in a poorly balanced book. Construction matters as much as selection.

How to Improve Portfolio Management Skills

1. Clear mandate: Define objective, horizon, constraints, and risk budget before you trade a share.

2. Allocation logic: Align position sizes with edge, correlation, and downside. Scale with evidence, not hope.

3. Risk overlays: Factor neutrality where needed, hedges for event risk, cash when dispersion dries up.

4. Measurement: Track hit rate, payoff ratio, factor exposures, active share, and attribution.

5. Review cycle: Rebalance on signals, not dates alone. Kill stale positions with no catalysts.

6. Improve with data: Post-trade analysis, variant perception logs, and checklists reduce repeated mistakes.

How to Display Portfolio Management Skills on Your Resume

12. MATLAB

MATLAB excels at numerical work—time series, optimization, and custom analytics that benefit from strong matrix operations.

Why It's Important

When you need rigorous quantitative analysis, MATLAB’s toolboxes and plotting capabilities bring clarity and speed.

How to Improve MATLAB Skills

1. Financial and econometric toolboxes: Pricing, risk metrics, filters, and forecasting—use built-ins to accelerate.

2. Data workflow: Import, clean, and structure data with scripts that run repeatably.

3. Visualization: Build charts that make trends and anomalies obvious. Annotate with context.

4. Optimization: Practice calibration, portfolio optimization, and robust parameter searches.

5. Documentation: Write functions with clear inputs/outputs, comments, and tests. Reuse beats rewrite.

6. Apply on real cases: Factor timing, event studies, regime detection—push from theory to production.

How to Display MATLAB Skills on Your Resume