StatisticsInterview Experiences

Same OA format as FDSE I think but onsite was stats focused, hypothesis testing and model evaluation metrics. Behavioral was embedded into every round, that was different. Coding bar felt pretty high.

SQL assessment was four questions, doable if you know window functions and CTEs. Power Day had two consecutive behavioral inetrviews about identifying unseen problems and explaining technical findings simply. Offer next morning

OA had two coding problems and the work simulation where you pick answers about leadership principles. Final round was brutal because the behavioral half they kept digging deeper on every answer like tell me more about that and what did you specifically do and I ran out of things to say. Coding was graph BFS which I got but apparently wasn't enough

First round was SQL with a window function question on ranked sales data. Second was a case on measuring sales rep performance from a CRM dataset

45 min on Teams they went through my resume and wanted to know about a REST API I built and leadership questions too, felt casual but took over a month to hear back

Pretty sure someone internal had a referral because they moved fast. Quick HR call then in office interview, mostly about past data work and why insurance. Some SQL conceptual questions and what tools I'd use to visualize claims data. Very casual process

They asked me to walk through how I'd clean a dataset with missing values and outliers. Phone screen last week and video call with the team yesterday. Python questions and also why Desjardins over other financial institutions

Waited months then got an interview invite in January for a position I applied to in September. 30 min behavioral interview on Zoom with two people, wanted to know what I know about the CRA and describe a time I analyzed a large dataset and also a 10 min written exercise after

Technical phone screen had SQL and a stats question on modeling surge pricing demand. Explained the approach fine but yeah

They care a lot about how you explain your approach and the tradeoffs you made. Recruiter screen then technical, OOP modelling of financial data, then a project showcase where I presented my best ML project. Good feedback but I didn't make the cut in a competitive cycle

They wanted my research background summarized in 90 seconds for the pre recorded video, plus two other timed questions. Multiple rounds after, behavioral and one technical on regression modeling and handling missing data. Waiting on final round feedback now

Phone screen with someone from data asked about experiment design and SQL. Technical round was a case on measuring delivery ETA accuracy.

Sustainability and safety came up, part of CN's brand. Behavioral and role specific questions about working under pressure and balancing multiple priorities. Hired hundreds of students annually so the competition exists but it's not brutal

AI chatbot did the initial screening before I talked to anyone human. Then a virtual interview about handling challenges and taking responsibility for mistakes. fairly generic, nothing data specific came up at all.

Asked about my resume in depth- past projects and how they connected to what I am studying

Screening call then CoderPad for an hour. The interviewer kept nudging when you got stuck on the SQL, appreciated that. Then an in-person day with 4 sessions, they gave a mini case about using data to improve a process

application took forever just to set up the account. Got an email for an interview like 3 months later and by that point I forgot I even applied. Two people on the call asking basic behavioral stuff, tell me about a time you worked on a team, how do you handle deadlines. Also some questions about databases which were easy. It was painfully slow and I already accepted something else by the time they got back to me

It was alright, but needed to grind a lot. Would recommend doing a lot of leetcode medium and easy and have a good understanding of the basics.

Smart interview recording then team interview. Behavioral and logical stuff. got the call a few days later

They dug deep into my past projects and specific design decisions. HR call first then the technical round.Some REST api questions too. Process felt organized and communication was good, just didn't make the cut

SQL and Python experience mattered a lot. Technical first with accounting and portfolio attribution, then behavioral qs later on

15 mins, really easy, heard it's way harder for FTEs with like 4 rounds but for intern ig they didn't really care all that much

No coding at all. Recruiter call, project discussion, culture round. Rejected, said they wanted a specific background

They really wanted to know what I knew about recent immigration targets and policy changes dumb for a co-op if u ask me. Behavioral interview about my data background and an example of using data to influence a decision. Competitive pool for this one

Data role covered JavaScript basics for some reason. HR interview first, then a technical screen. SQL manipulation questions too. Behavioral and personality stuff in HR. Communication from the recruiter was delayed a couple times

Standard behavioral stuff, why Bank of Canada and a prioritizing tasks scenario. Panel format, rotating questioners. HR call before that was quick