Top 12 Investment Analyst Skills to Put on Your Resume

In the competitive field of investment analysis, blending technical horsepower with clear thinking and crisp communication gives your resume teeth. The skills below carry weight in interviews, speed up analysis, and turn messy data into decisions that move portfolios.

Investment Analyst Skills

  1. Excel
  2. Bloomberg Terminal
  3. Python
  4. SQL
  5. R
  6. Tableau
  7. MATLAB
  8. Financial Modeling
  9. VBA
  10. SAS
  11. Power BI
  12. Quantitative Analysis

1. Excel

Excel anchors day-to-day analysis: cleaning data, building models, stress-testing assumptions, and packaging results fast. It’s the analyst’s swiss army knife.

Why It's Important

Because it’s everywhere, flexible, and fast for iteration. From ad hoc analysis to valuation builds, Excel shortens the distance between question and answer.

How to Improve Excel Skills

Level up with what matters most for finance work:

  1. Modern functions: XLOOKUP, FILTER, INDEX/MATCH, OFFSET, LET, LAMBDA, dynamic arrays. Fewer helper columns, clearer logic.

  2. Data shaping: Power Query for extraction and cleaning; Power Pivot for data models and relationships across large tables.

  3. Pivots and summaries: PivotTables/PivotCharts for fast aggregation, grouping, and drill-down.

  4. Visualization: Clean charts, sparklines, conditional formatting, thoughtful layout. Dashboards that highlight signal, not glitter.

  5. Model discipline: Consistent color conventions, separation of inputs/logic/outputs, version control, and audit checks.

  6. Macros where it counts: Record and refine simple automations; keep them robust and documented.

  7. Speed: Keyboard shortcuts, named ranges, and efficient formulas to tame big workbooks.

How to Display Excel Skills on Your Resume

How to Display Excel Skills on Your Resume

2. Bloomberg Terminal

A real-time gateway to markets, companies, credit, rates, commodities, and news—plus analytics that cut through noise. It’s more than data; it’s a workflow.

Why It's Important

Speed and depth. From price discovery to corporate actions, ESG fields, curves, and event tracking, it centralizes what analysts chase all day.

How to Improve Bloomberg Terminal Skills

  1. Own the basics: Navigation, launchpad layouts, keyboard shortcuts, and the HELP key. Save custom screens for your asset class.

  2. Use BQL and screening: Build repeatable data pulls and equity/credit screens with clear criteria you can explain.

  3. Excel add-in: Parameterized formulas, refresh schedules, and clean ranges that feed models without breaking.

  4. Function fluency: Drill into FA, WEI, RV, EQS, CRVF, ECO, and MRA functions relevant to your coverage.

  5. Alerts and monitoring: Price, news, and calendar alerts that actually matter—earnings, filings, liquidity cues.

  6. Documentation: Keep a personal cheat sheet of functions, tickers, and workflows so handoffs and audits are painless.

How to Display Bloomberg Terminal Skills on Your Resume

How to Display Bloomberg Terminal Skills on Your Resume

3. Python

Clean data, stitch APIs, run stats, backtest ideas, and automate the grunt work. Python turns repetition into a script and models into living tools.

Why It's Important

It scales. From quick checks to full pipelines and machine learning, Python keeps analyses reproducible and auditable.

How to Improve Python Skills

  1. Core stack: Get comfortable with pandas, NumPy, SciPy, statsmodels, scikit-learn. Understand indexes, joins, vectorization.

  2. Time series: Resampling, rolling windows, seasonality, stationarity tests, and feature engineering for financial data.

  3. Data access: APIs, database connectors, and file ingestion that handle messy, real-world data reliably.

  4. Visualization: Matplotlib, Seaborn, Plotly for crisp charts and exploratory analysis.

  5. Notebooks to packages: Start in Jupyter, then refactor into modules, tests, and configs. Reuse beats rewrite.

  6. Performance: Profiling, vectorized code, and where appropriate, multiprocessing.

  7. Project work: Build mini-tools: factor models, ETF screeners, event studies, option pricers. Ship them internally.

How to Display Python Skills on Your Resume

How to Display Python Skills on Your Resume

4. SQL

The language of structured data. Pull, filter, aggregate, and reconcile large datasets without dragging them into spreadsheets first.

Why It's Important

You can answer questions straight from source systems, reproducibly and fast—vital for audit trails and scale.

How to Improve SQL Skills

  1. Foundations: SELECT, WHERE, GROUP BY, HAVING, ORDER BY. Clean, readable queries with clear aliases.

  2. Advanced queries: Window functions, CTEs, subqueries, pivots/unpivots. Solve problems without procedural hacks.

  3. Performance: Indexing, JOIN strategies, EXPLAIN plans, appropriate data types. Small habits, big speed gains.

  4. Model awareness: Know the schema and keys. Understand grain, slowly changing dimensions, and data lineage.

  5. Security and quality: Roles, row-level controls, validation checks, and reconciliation queries you can reuse.

  6. BI connections: Pipe SQL outputs cleanly into Excel, Tableau, or Power BI for downstream use.

How to Display SQL Skills on Your Resume

How to Display SQL Skills on Your Resume

5. R

Purpose-built for statistics and plotting. Great for research workflows, reproducible reports, and rigorous time-series analysis.

Why It's Important

R shines when depth of statistical treatment matters—factor studies, event analysis, risk modeling, and tidy reporting.

How to Improve R Skills

  1. Tidy workflow: Master tidyverse, data.table for speed, and piping for readable transformations.

  2. Visualization: ggplot2 with thoughtful themes, facets, and annotations that tell a clear story.

  3. Finance packages: xts, zoo, quantmod, TTR, PerformanceAnalytics, PortfolioAnalytics. Work with returns, risk, and optimization.

  4. Reproducibility: RMarkdown and Quarto for reports; packrat/renv for dependency management.

  5. Modeling: tidymodels, xgboost, caret for predictive work with proper resampling and diagnostics.

  6. Shiny: Lightweight apps for internal dashboards and scenario tools.

How to Display R Skills on Your Resume

How to Display R Skills on Your Resume

6. Tableau

Turn complex data into interactive dashboards that decision-makers can explore without breaking anything.

Why It's Important

It shortens the feedback loop between analysis and action. Patterns pop. Outliers shout. Stakeholders engage.

How to Improve Tableau Skills

  1. Data modeling: Clean star schemas, data source filters, and extracts tuned for performance.

  2. Calculations: Table calcs, level of detail (LOD) expressions, parameters, and date intelligence for finance-friendly views.

  3. Design: Layouts with purpose—KPIs up front, clear drill paths, minimal clutter, thoughtful color.

  4. Interactivity: Actions, tooltips, and parameter controls that guide exploration without confusing users.

  5. Performance: Performance Recorder, optimized joins, and aggregated extracts. Fast feels better.

How to Display Tableau Skills on Your Resume

How to Display Tableau Skills on Your Resume

7. MATLAB

Numerical computing for heavy math, optimization, and simulation—particularly handy in quant research and structured products.

Why It's Important

It offers mature toolboxes for econometrics, optimization, and signal processing with reliable, production-grade numerics.

How to Improve MATLAB Skills

  1. Toolboxes that matter: Financial, Econometrics, Optimization. Build, test, and compare models cleanly.

  2. Time-series flow: Work with timetables, synchronized series, and robust missing-data handling.

  3. Automation: Script repeatable workflows, parameter sweeps, and reporting hooks.

  4. Prototyping to production: Profile code, vectorize, and leverage parallel computing when workloads balloon.

  5. Backtesting discipline: Clear splits, walk-forward validation, and careful control of look-ahead bias.

How to Display MATLAB Skills on Your Resume

How to Display MATLAB Skills on Your Resume

8. Financial Modeling

Translate business drivers into numbers. Forecast cash flows, gauge value, test scenarios, and frame risk—clearly and defensibly.

Why It's Important

Models are decision engines. They connect assumptions to outcomes so teams can argue productively and act confidently.

How to Improve Financial Modeling Skills

  1. Accounting fluency: Link the three statements, understand working capital mechanics, taxes, and stock comp nuance.

  2. Structure: Inputs → calculations → outputs. No hard-coding. Transparent labels. Error flags and audit trails.

  3. Valuation toolkit: DCF, trading comps, deal comps, LBO, sum-of-the-parts. Know when each is appropriate.

  4. Sensitivity and scenarios: Data tables, switches, and scenario managers that don’t crumble under change.

  5. Checks and controls: Balance tie-outs, circularity management, and sanity tests. Trust comes from control.

  6. Storytelling: Clean outputs, bridge charts, and commentary that highlight drivers, not just numbers.

How to Display Financial Modeling Skills on Your Resume

How to Display Financial Modeling Skills on Your Resume

9. VBA

When Excel needs a motor, VBA delivers. Automate repeat tasks, stitch processes, and build tools your team actually uses.

Why It's Important

It slashes manual work, reduces errors, and standardizes repeatable workflows across models and reports.

How to Improve VBA Skills

  1. Clean code: Naming conventions, modules, and comments. Small, testable procedures over sprawling macros.

  2. Automation targets: Import routines, formatting, reconciliation, scenario switches, and report assembly.

  3. Error handling: Structured error traps, logging, and user prompts that guide, not confuse.

  4. Data handling: Work with arrays, dictionaries, and Power Query handoffs for speed and stability.

  5. UX basics: Simple forms, buttons, and status messages to make tools approachable.

How to Display VBA Skills on Your Resume

How to Display VBA Skills on Your Resume

10. SAS

A stalwart in regulated analytics and large-scale data environments, especially in risk, credit, and compliance workflows.

Why It's Important

It offers robust procedures, governance, and repeatability—critical where auditability and controls are non-negotiable.

How to Improve SAS Skills

  1. Core proficiency: DATA step, PROC SQL, joins, reshaping, and macros for parameterized workflows.

  2. Time-series and forecasting: ETS/ARIMA procedures, seasonality handling, and model diagnostics.

  3. Stat routines: Regression, distributions, and univariate profiling for quick health checks on data.

  4. Data management: Clean pipelines, metadata hygiene, and documented lineage from source to output.

  5. Modern stack: Familiarity with SAS Viya and integration points with Python/R where that makes sense.

  6. Practice: Apply on real datasets—portfolio risk, credit scoring, stress tests—and critique your outputs.

How to Display SAS Skills on Your Resume

How to Display SAS Skills on Your Resume

11. Power BI

From raw data to interactive reports with refresh schedules and row-level security—great for executive-ready insights at scale.

Why It's Important

It centralizes KPIs and trends with governance, making recurring reporting fast, consistent, and shareable.

How to Improve Power BI Skills

  1. DAX depth: Time intelligence, iterators, filter context, calculation groups. Finance math, done right.

  2. Data modeling: Star schemas, proper relationships, surrogate keys, and a clean semantic layer.

  3. Power Query (M): Resilient transformations, parameterized queries, and source control for refresh pipelines.

  4. Performance tuning: Vertipaq Analyzer concepts, summarization, and incremental refresh for large models.

  5. Governance: RLS/OLS, workspaces, endorsements, and refresh cadences that teams can trust.

How to Display Power BI Skills on Your Resume

How to Display Power BI Skills on Your Resume

12. Quantitative Analysis

Numbers with rigor. Models with guardrails. Turning uncertainty into distributions and decisions.

Why It's Important

It brings structure to ambiguity—measuring risk, estimating return, and stress-testing strategies before capital is at stake.

How to Improve Quantitative Analysis Skills

  1. Math and stats backbone: Probability, linear algebra, calculus, hypothesis testing, and inference you can explain in plain English.

  2. Financial theory: CAPM, factor models, term structure, option pricing, and portfolio optimization with realistic constraints.

  3. Simulation and backtesting: Monte Carlo, bootstrap resampling, walk-forward validation, and tough rules against look-ahead bias.

  4. Risk metrics: Volatility, drawdown, VaR/CVaR, tracking error, information ratio, stability over multiple regimes.

  5. Data integrity: Survivorship bias traps, corporate actions, stale prices, and outlier handling that doesn’t sanitize away risk.

  6. Practice on real problems: Paper trade, build small research notes, and pressure-test your assumptions with peers.

  7. Community: Engage with practitioner groups and platforms focused on systematic investing and research (e.g., CFA societies, quant forums, QuantConnect).

How to Display Quantitative Analysis Skills on Your Resume

How to Display Quantitative Analysis Skills on Your Resume
Top 12 Investment Analyst Skills to Put on Your Resume