Bank of America Quantitative Analyst Interview Guide

The short answer: Bank of America's Quantitative Finance Analyst is a bank-wide job profile, and most US postings sit in Global Risk Analytics, which builds market risk, counterparty risk and credit models. Front office quant analysts sit in Global Markets' Quantitative Strategies & Data Group (QSDG). Bank of America says campus candidates apply online, may take an assessment, then have first and second-round interviews that can include an on-demand recorded video interview, and a final round with the business. The video is mostly behavioral. What the final round tests comes from one candidate prep guide and one candidate-reported question collection: probability, coding, statistics and options pricing. Last reviewed October 2026.

Bank of America quantitative analyst interview: quick answers

The Bank of America quantitative analyst role

What Bank of America quantitative analysts work on, the skills its job postings ask for, and what a week can look like. Bank of America posts the role as Quantitative Finance Analyst, a bank-wide profile mostly in Global Risk Analytics, and Quantitative Analyst or Quantitative Strategist in Global Markets Quantitative Strategies & Data Group (QSDG).

Bank of America quantitative analyst levels and pay

Your level sets the bar you are interviewed against and the pay band of the offer.

The Quantitative Finance ladder runs from Quantitative Finance Analyst to Sr. Quantitative Finance Manager. Corporate titles such as Assistant Vice President and Vice President appear as prefixes on some postings. The front office QSDG posting uses Associate and VP, with one range for both.

Pay in Bank of America's US job postings

Bank of America lists an annualized pay range on its US postings, with offers based on experience, education and skill set. Every posting with a range says the role is discretionary incentive eligible. Rows marked Risk are Global Risk Management roles; the last row is front office.

Multi-location postings show one range without saying which location it applies to. Two more Quantitative Finance Analyst postings show $89.8K to $155K and $89.8K to $151.2K: one is an AI data support role and the other names no team, so they are left out. The Vice President; Quantitative Finance Analyst posting in Chicago and one Charlotte posting show no range, and campus postings show no pay. Ranges seen October 29, 2026.

Bank of America quantitative analyst interview process

The steps follow Bank of America's student application process page and hiring FAQs. The content of the final round comes from one candidate prep guide, which says it draws on public information and candidate patterns and gives no report count, and from one candidate-reported question collection.

Based on Bank of America's own pages and candidate reports.

For experienced hires, Bank of America says interviews mix phone calls, in-person conversations and video interviews with HR, business managers and possibly peers, and may include exercises that measure aptitudes and values. It does not publish who makes the final decision. Last reviewed October 2026.

What is different at Bank of America

• Quantitative Finance Analyst is a bank-wide job profile with its own ladder: Quantitative Finance Analyst, Sr. Quantitative Finance Analyst, Quantitative Finance Manager and Sr. Quantitative Finance Manager. Most US postings sit in Global Risk Analytics, the risk and capital modeling arm of Global Risk Management. The title alone does not fix the work: one Charlotte posting with it is an AI data and prototyping support role.
• Front office quants sit in Global Markets' Quantitative Strategies & Data Group, which describes its work as the intersection of quant finance, data science and AI. Postings there use titles such as Associate/VP, Quantitative Analyst - Commodities, and QSDG summer associates work as quantitative strategists on one product area. Global Quantitative Research is a separate research-side program in Global Research.
• Some "quantitative" titles are other jobs. Quantitative Engineer roles in Global Risk build reusable data and analytics software, closer to a quant developer. Client Quantitative Analyst I is business data analytics in SQL, SAS and Python. In QDAP, only the Quantitative Analyst profile fits this role; the Data Analyst profile does not.
• Global Risk Analytics covers several model families. Market Risk Quants build VaR, Stressed VaR, Risks Not in VaR and FRTB models plus CCAR stress testing. Counterparty credit risk quants build risk factor simulation, pricing and aggregation models for PFE and IMM. Consumer Model Development and Operations builds default, EAD and LGD models with regression and tree-based ML such as XGBoost and LightGBM.
• The on-demand recorded video interview has published rules. It takes about 20 to 30 minutes, with 30 seconds to prepare and up to three minutes per answer and no follow-ups. Bank of America says notes are fine, but you should not read a script. Campus candidates may apply to one office and one division per year.
• Bank of America does not publish a rule on AI use in interviews; ask your recruiter. Expect AI as a topic: QSDG summer associates may use agentic AI workflows, and one Quantitative Finance Analyst posting supports AI data and prototyping work.

Bank of America quantitative analyst interview questions

Questions from our bank, then practice prompts we wrote for this guide around Bank of America's work.

1import math
2
3def exposure_profile(trades, q=0.95):
4    """Return {"ee": [...], "pfe": [...], "epe": float, "peak_pfe": float}."""
5    pass

1import math
2
3def exposure_profile(trades, q=0.95):
4    if not trades or not trades[0] or not trades[0][0]:
5        raise ValueError('need at least one trade, scenario and date')
6    if not 0 < q < 1:
7        raise ValueError('q must be between 0 and 1')
8    n_s, n_t = len(trades[0]), len(trades[0][0])
9    if any(len(t) != n_s or any(len(row) != n_t for row in t) for t in trades):
10        raise ValueError('every trade needs the same scenarios and dates')
11    k = math.ceil(round(q * n_s, 9)) - 1
12    ee, pfe = [], []
13    for j in range(n_t):
14        exposure = sorted(max(sum(t[s][j] for t in trades), 0.0) for s in range(n_s))
15        ee.append(round(sum(exposure) / n_s, 4))
16        pfe.append(round(exposure[k], 4))
17    return {'ee': ee, 'pfe': pfe, 'epe': round(sum(ee) / n_t, 4), 'peak_pfe': max(pfe)}
18
19# Complexity: O(d s (m + log s)) time for d dates, s scenarios and m trades, O(s + d) space.

How to prepare

A plan for the Bank of America loop, most important first:

1. Find out whether you are interviewing for Global Risk Analytics or front office QSDG, and read that team's posting closely.
2. For risk roles, review VaR, Stressed VaR, FRTB, counterparty exposure and credit models for CCAR and CECL.
3. For QSDG, review option pricing, stochastic modelling and numerical methods, and practice in Python.
4. Practice deriving a result and then coding it, which candidate sources say final rounds expect.
5. Rehearse behavioral answers for the on-demand recorded video, using the 30 seconds to plan and about two minutes to answer.
6. Drill probability, statistics and time series questions out loud with a check on each answer.

Practice path

Courses that cover the rounds above:

• Financial Mathematics
• Probability for Quant Interviews
• Time Series Forecasting
• Applied Statistics
• Advanced Statistics