Top 12 Securities Analyst Skills to Put on Your Resume

In today's competitive job market, standing out as a securities analyst takes a nimble stack of technical depth and people sense. Showcasing the right skills on your resume signals real capability—market intuition, model fluency, clean storytelling, the whole toolkit.

Securities Analyst Skills

1. Bloomberg Terminal
2. Python
3. SQL
4. Excel (Advanced)
5. MATLAB
6. R
7. Tableau
8. SAS
9. Financial Modeling
10. Quantitative Analysis
11. Risk Management
12. VBA

1. Bloomberg Terminal

The Bloomberg Terminal is a subscription platform that delivers real-time and historical market data, news, analytics, trading, and messaging. Analysts lean on it for discovery, monitoring, valuation, and execution support.

Why It's Important

It’s a single cockpit for price discovery, liquidity, fundamentals, analytics, and breaking news—letting you test ideas quickly, compare peers, track portfolios, and make informed calls under time pressure.

How to Improve Bloomberg Terminal Skills

1. Learn core functions cold: DES, FA, WEI, HP, RV, EQS, CRP, HDS, GP, ECO, NI, TOP, FLDS. Muscle memory saves minutes that matter.

2. Build focused monitors and alerts: custom Market Monitors, price/volume/news alerts, and watchlists. Let the system tap you on the shoulder when thresholds hit.

3. Excel Add-In proficiency: BDP, BDH, BDS, overrides, field search (FLDS), and refresh controls. Wire models to live data without breaking audit trails.

4. Workflow ergonomics: keyboard shortcuts, custom launch panels, color-coded screens, split panes, and messaging. Reduce clicks, increase signal.

5. Portfolio and scenario tools: PORT for attribution and risk, SPLC for supply chains, EVTS for event study angles. Connect headlines to exposures with intent.

6. Training and diagnostics: use on-terminal help, function guides, and Bloomberg Market Concepts. Practice daily with real tickers and live constraints.

How to Display Bloomberg Terminal Skills on Your Resume

2. Python

Python is a flexible programming language used to clean, transform, and analyze data; build models; automate workflows; and prototype research quickly.

Why It's Important

It accelerates data ingestion, testing of hypotheses, backtesting, and reporting. Less manual grind, more repeatable analysis, faster iteration.

How to Improve Python Skills

1. Core fluency: data types, functions, classes, iterators, comprehensions, packaging, virtual environments. Write clear, modular code.

2. Data stack mastery: pandas (or Polars for speed), NumPy, SciPy, statsmodels, scikit-learn, pandas time series. Handle messy, time-indexed financial data gracefully.

3. Visualization that persuades: Matplotlib, Seaborn, Plotly. Build charts that answer a question, not just decorate it.

4. Backtesting and research: vectorbt or Backtrader for ideas; beware look-ahead bias and overfitting; enforce out-of-sample and walk-forward testing.

5. Performance and reliability: vectorization, profiling, type hints (mypy), testing (pytest), linting/formatting (ruff/black). Speed and safety beat cleverness.

6. Workflow polish: Jupyter for exploration, VS Code for projects, Git for version control, data contracts for inputs/outputs.

How to Display Python Skills on Your Resume

3. SQL

SQL is the language for querying and shaping relational data. It’s the backbone for pulling, joining, aggregating, and validating the datasets your models live on.

Why It's Important

Clean, efficient queries unlock timely insights. Poor queries bury signal in latency and noise. SQL is how you get truth out of warehouses.

How to Improve SQL Skills

1. Get the grammar right: joins, filters, grouping, subqueries, CTEs, window functions, conditional aggregation.

2. Think in sets: write queries that scale; avoid row-by-row logic. Use window functions for time-aware calcs like rolling returns and ranks.

3. Performance intuition: indexing, partitioning, clustering, statistics, query plans. Know why a query is slow, then fix it.

4. Dialect awareness: PostgreSQL, SQL Server, Snowflake, BigQuery—small differences, big surprises. Test assumptions.

5. Data hygiene: dedupe keys, handle missing and late-arriving data, timezone and calendar edge cases, idempotent pipelines.

How to Display SQL Skills on Your Resume

4. Excel (Advanced)

Advanced Excel means building reliable, auditable models with speed—blending formulas, data modeling, and automation to analyze securities and portfolios.

Why It's Important

It’s still the lingua franca on deal teams and in research reviews. Fast pivots, crisp summaries, zero broken links.

How to Improve Excel (Advanced) Skills

1. Modern functions: XLOOKUP, XMATCH, dynamic arrays (FILTER, SORT, UNIQUE), LET, LAMBDA. Fewer helper columns, clearer intent.

2. Power Query for ETL: import, clean, and reshape data repeatably; parameterize and document steps.

3. Power Pivot and data models: relationships, measures (DAX), star schemas. Scale beyond flat files.

4. PivotTables at full throttle: calculated fields, groupings, slicers, timelines, show values as (YoY, % of total).

5. Automation where it counts: judicious VBA, templates, and named ranges. Keep calculation settings and error checks front and center.

6. Charts that punch: combo charts, secondary axes used sparingly, dynamic ranges, consistent number formatting.

How to Display Excel (Advanced) Skills on Your Resume

5. MATLAB

MATLAB is a numerical computing environment for matrix math, simulations, signal processing, and visualization—well-suited to time series and quantitative finance workflows.

Why It's Important

It delivers robust toolboxes for pricing, risk, optimization, and econometrics, with fast prototyping and strong plotting—handy for research-grade analysis.

How to Improve MATLAB Skills

1. Toolbox depth: Financial, Econometrics, Optimization, Statistics and Machine Learning. Use the right function instead of reinventing it.

2. Time series mastery: timetables, synchronization, resampling, and missing data strategies designed for market data quirks.

3. Vectorization and performance: preallocation, bsxfun-style thinking, parallel computing when loops groan.

4. Live scripts and reports: literate analysis with narrative, code, and figures in one place. Easier review, fewer misunderstandings.

5. Interoperability: exchange with Python via the engine API or use MATLAB for the heavy numerics and export results downstream.

How to Display MATLAB Skills on Your Resume

6. R

R is a language and ecosystem for statistics and graphics, loved for reproducible research, tidy data workflows, and sharp visuals.

Why It's Important

It shines in rigorous statistical testing, time series modeling, factor research, and report-ready plots—making complex results readable.

How to Improve R Skills

1. Data fluency: dplyr and data.table for fast transformations; tidyr for reshaping; stringr and lubridate for text and dates.

2. Visualization craft: ggplot2 with themes, scales, facets, and annotations that tell a story without shouting.

3. Time series and finance: xts, zoo, quantmod, TTR; roll your indicators carefully and align calendars.

4. Modeling toolkit: stats, forecast or fable, glmnet, broom to tidy outputs; validate with holdouts and cross-validation.

5. Reproducibility: scripts into projects, renv for dependencies, Quarto or R Markdown for literate analysis, Shiny for interactive dashboards.

How to Display R Skills on Your Resume

7. Tableau

Tableau turns dense data into interactive visuals and dashboards that decision-makers actually use.

Why It's Important

Good dashboards compress time. They surface trends, anomalies, and drilldowns so portfolio calls and stock notes come together faster.

How to Improve Tableau Skills

1. Data model sense: use relationships before joins when appropriate, define clean grains, and keep extract sizes in check.

2. Advanced calculations: table calcs, LOD expressions, parameters, sets, and actions. Interactivity that feels natural, not gimmicky.

3. Design for finance: consistent formats, axis discipline, reference bands, sparklines, and tooltips that carry context.

4. Performance tuning: minimize quick filters, reduce high-cardinality dimensions, optimize extracts, and leverage Performance Recording.

5. Distribution: publish with permissions, data source certification, and a refresh schedule that matches market cadence.

How to Display Tableau Skills on Your Resume

8. SAS

SAS is a platform for data management, statistics, and modeling—common in regulated environments and legacy analytics stacks.

Why It's Important

It offers stable, well-audited procedures and strong data handling—useful when controls and lineage matter as much as speed.

How to Improve SAS Skills

1. Base SAS and PROC SQL: import/export, merges, reshapes, and robust query patterns.

2. Analytical procedures: REG, LOGISTIC, ARIMA, TIMESERIES; know assumptions and diagnostics, not just button presses.

3. Macro language and automation: parameterize repetitive jobs, build reusable utilities, organize libraries and formats coherently.

4. Performance and governance: indexes, compression, proper sorting, and clear logs; document lineage for audit trails.

5. Interoperability: pass data to Python/R when beneficial; keep SAS as the orchestration layer where governance requires it.

How to Display SAS Skills on Your Resume

9. Financial Modeling

Financial modeling builds structured representations of a business or asset to forecast performance and value—often in Excel, sometimes supported by code.

Why It's Important

It links assumptions to outcomes. With a good model you can pressure-test narratives, price risk, and explain results without hand-waving.

How to Improve Financial Modeling Skills

1. Three-statement spine: clean income statement, balance sheet, cash flow with robust links; avoid hardcodes, surface assumptions.

2. Valuation suite: DCF with explicit drivers, comps and precedents with apples-to-apples adjustments, and sanity checks across methods.

3. Schedules that matter: revenue build, working capital, capex and depreciation, debt and interest, stock comp and dilution.

4. Scenario and sensitivity: toggles for cases, data tables for key drivers, and clear outputs for ranges—not just point estimates.

5. Quality control: error checks, circularity management, consistent units, version control, and documentation that someone else can follow.

How to Display Financial Modeling Skills on Your Resume

10. Quantitative Analysis

Quantitative analysis applies math and statistics to markets—estimating relationships, testing signals, measuring risk, and guiding allocation.

Why It's Important

Numbers keep bias in check. With robust methods, you separate noise from information and avoid being fooled by chance.

How to Improve Quantitative Analysis Skills

1. Core math: probability, linear algebra, calculus, optimization. Build intuition, not rote formulas.

2. Time-series know-how: stationarity, ARIMA/VAR, volatility models like GARCH; respect regime shifts and structural breaks.

3. Factor thinking: CAPM and multi-factor models, risk premia, exposures, and attribution that ties to portfolio outcomes.

4. Validation discipline: out-of-sample tests, cross-validation, walk-forward, realistic transaction costs and slippage.

5. Risk and tail awareness: VaR and Expected Shortfall with limitations acknowledged, scenario analysis, and stress tests that bite.

How to Display Quantitative Analysis Skills on Your Resume

11. Risk Management

Risk management identifies, measures, and controls exposures that can derail returns—market, credit, liquidity, operational, and model risk among them.

Why It's Important

It protects capital and steadies decision-making. Better downside math, fewer nasty surprises, more durable performance.

How to Improve Risk Management Skills

1. Measurement rigor: factor exposures, duration/convexity, Greeks for options, concentration metrics, liquidity screens.

2. Scenarios and stresses: macro shocks, idiosyncratic blowups, correlation spikes; predefine playbooks and thresholds.

3. Controls and policy: limit frameworks, escalation paths, independent review, and model risk governance with documentation.

4. Hedging and mitigation: options overlays, futures, pair trades, diversification that’s real (not just many tickers).

5. Stay current: accounting and regulatory changes, market microstructure shifts, and new risk tools that sharpen measurement.

How to Display Risk Management Skills on Your Resume

12. VBA

VBA (Visual Basic for Applications) automates tasks in Excel and shapes custom functions, forms, and workflows that analysts run every day.

Why It's Important

It turns repetitive steps into one-click routines and enforces consistency. Faster analyses, fewer manual errors.

How to Improve VBA Skills

1. Know the object model: workbooks, worksheets, ranges, charts, and events. Navigate without guesswork.

2. Write robust code: structured modules, Option Explicit, error handling, logging, and input validation.

3. Performance habits: arrays over cell-by-cell loops, turn off screen updating and calculation where safe, minimize selects.

4. Reusability: user-defined functions, class modules for repeated patterns, configuration driven parameters.

5. Integration: pull data from databases or APIs, interact with the Excel Data Model, and respect 64-bit and macro security constraints.

How to Display VBA Skills on Your Resume