Analyzing and interpreting data; Framing and synthesis. [43]

Quantitative Analyst

What this job does:

Use statistical and mathematical modeling to evaluate risk, price assets, optimize portfolios or strategies, and build analytics tools for investing, trading, or risk management.

This job is similar to these lab/research tasks:

Research: build models, run simulations, explore parameter regimes; Data: clean and join large datasets, version data, automate ETL; Risk/scenarios: sensitivity analyses, error propagation, stress tests; Tooling: write reusable libraries, optimize runtime, add tests; Other: document methods, present results and defend assumptions.

Typical starting salary range

$161k to $255k

Salary estimate represented as 25th to 75th percentile. Gathered from recent job postings, Glassdoor.com, and Salary.com

Daily task breakdown

Quant research & model development 35%
Data work (market data prep, feature engineering, backtesting) 25%
Risk/portfolio analytics & scenario analysis 20%
Tooling/production code improvements 10%
Other (documentation, presentations, governance) 10%.

Skills you'll use in this job:

Strong math/stats; Python (often plus C++); experience with large datasets and backtesting; domain knowledge in markets/risk; ability to communicate model assumptions and limitations; strong software engineering hygiene.

Talk about these PhD skills in your resume and interview:

Translate your PhD to rigorous modeling: formulate the problem, choose/derive models, validate with simulation/held-out data, and communicate assumptions. Highlight reproducibility, careful data QC, and experience building tools used by others.