
Bmo Harris Bank Data Analyst interview typically runs 2-3 rounds: HR screening, manager interview, and sometimes a HireVue or assessment. The process usually takes a few weeks and is fairly automated and fit-focused.
$73K
Avg. Base Comp
$123K
Avg. Total Comp
3-4
Typical Rounds
3-5 weeks
Process Length
Our candidates report that Bmo Harris Bank is less interested in dazzling technical depth than in whether you can operate comfortably in a very practical, relationship-heavy environment. Multiple experiences mention basic SQL fundamentals — things like joins, HAVING, and simple table-to-table logic — alongside resume walkthroughs and questions about difficult cross-functional partners or customers. That tells us the bar is solid working fluency, not advanced analytics theory. We’ve also seen Power BI and other tools come up as proof that you can contribute immediately with the stack the team already uses.
A recurring theme is the company’s emphasis on culture and responsiveness. One candidate was explicitly told the team worked “like a family” and that people would call each other at midnight, which is a strong signal that availability and flexibility may matter as much as technical competence. Another candidate described the process as friendly but more of a fit check than a deep screen, and that matches the overall pattern: they seem to care a lot about how you communicate, how you handle friction, and whether your expectations line up with the role’s pace and compensation. In our view, the non-obvious make-or-break factor here is not the SQL question itself — it’s whether your answers and demeanor suggest you’ll thrive in a hands-on, always-on banking team.
Synthetized from 3 candidates reports by our editorial team.
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Topics based on recent interview experiences.
Featured question at Bmo Harris Bank
How would we build a model to detect fraud and text customers to approve or deny fraudulent transactions
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| Bagging vs Boosting | |
| Check Normality | |
| 2nd Highest Salary | |
| Empty Neighborhoods | |
| Rolling Bank Transactions | |
| Comments Histogram | |
| Employee Salaries | |
| Closest SAT Scores | |
| Top Three Salaries | |
| Slacking Employees Salaries | |
| Experiment Validity | |
| Find the Missing Number | |
| Compute Deviation | |
| Prime to N | |
| Last Transaction | |
| Department Expenses | |
| 500 Cards | |
| Session Difference | |
| Random SQL Sample | |
| Rain in N Days | |
| Subscription Overlap | |
| Paired Products | |
| Hurdles In Data Projects | |
| Swipe Precision | |
| Over-Budget Projects | |
| P-value to a Layman | |
| Third Purchase | |
| Size of Joins | |
| Top 3 Users |
Synthesized from candidate reports. Individual experiences may vary.
The process typically starts with an HR screening call to review your background, experience, and general fit for the Data Analyst role. This stage is mostly behavioral and may include questions about your resume, interest in the position, and how you handle conflict or difficult stakeholders.
Some candidates complete an automated HireVue interview with recorded responses instead of a live conversation. Questions are non-technical and focus on motivation, past challenges, and behavioral examples, with one reattempt allowed per recorded answer.
Candidates may then take a timed HackerRank assessment that includes a coding challenge, a database/SQL challenge, and multiple-choice questions. The assessment appears to function as a screening test and covers practical fundamentals rather than advanced analytics.
Later rounds are typically with the hiring manager and sometimes another manager. These conversations mix behavioral questions with basic technical checks such as SQL joins, HAVING, and experience with tools like Power BI, while also evaluating communication style and fit with the team.