
LSEG AI Research Scientist interview typically runs 3 rounds: pre-recorded interview, video call, and take-home assignment. The process spans roughly 1–2 weeks and is notable for poor post-assignment communication.
$151K
Avg. Base Comp
$205K
Avg. Total Comp
3
Typical Rounds
2-3 weeks
Process Length
Our candidates report that LSEG's interview style for AI Research Scientist roles leans heavily on judgment and contextual reasoning rather than technical depth. The one question we have on record — a broad prompt about whether sanctions are good — is telling. It suggests the interviewers are probing how you reason about real-world consequences in a regulated environment, not whether you can recite model architectures. For a role at a major financial market infrastructure company, that makes sense: the stakes of deploying AI in compliance-adjacent contexts are high, and LSEG appears to want researchers who understand that.
The more important pattern here is the disconnect between the warmth of the interview and the chaos of the process. The candidate we spoke with was explicitly told to expect an assignment and next steps, then received an automated rejection the very next day — before they had even submitted the work. They completed the take-home anyway and were subsequently ghosted after following up. This isn't just a bad candidate experience; it's a signal that internal coordination between hiring teams and automated systems is unreliable, and that positive verbal feedback from interviewers should not be taken as a reliable indicator of where you actually stand.
We'd go in with eyes open. The pre-recorded screen and the video conversation may feel encouraging, but the process can stall or collapse without explanation. The take-home turnaround is tight — two days — so having a clear framework for connecting AI methodology to finance-specific constraints will matter more than raw technical output.
Synthetized from 1 candidates reports by our editorial team.
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Real interview reports from people who went through the Lseg (london stock exchange group) process.
Had a pleasant experience with the process overall, even though the ending was frustrating. I was first contacted over email in early January 2025 and asked to complete a pre-recorded interview. A few days later, I was invited to a video call, and that round went quite well — the interviewers were friendly and the conversation felt smooth. They said they would send me an assignment afterward, and if that went well, we would discuss the next steps for joining the team. The assignment arrived almost immediately after the second interview, and I was given two days to finish it, which felt pretty tight but manageable.
What stood out most was that the day after the video call, I got an automated email saying I was no longer being considered for the role, even though I had just been told there would be an assignment and next steps. I still completed the assessment and sent it in anyway, but then I heard nothing back for one to two weeks. I followed up by email to ask what I should expect, and after that I was basically ghosted. The only actual interview question I remember was a broad opinion question about whether sanctions are good, so it felt more like a discussion of judgment and reasoning than a technical screen. Overall, the process was polite at first but ended very poorly, and I’d go in expecting a pre-recorded round, a friendly video interview, and then a short take-home assignment with very uncertain communication after that.
Prep tip from this candidate
Be ready for a broad judgment-style question like whether sanctions are good, and expect a take-home assignment with a very short turnaround. I’d also prepare for the possibility that communication after the video round may be inconsistent, so clarify next steps before investing too much time.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Lseg (london stock exchange group)
Describing a data project and its challenges
| Question | |
|---|---|
| Testing Constraints | |
| Your Strengths and Weaknesses | |
| Data Cleaning Experiences | |
| Why Do You Want to Work With Us | |
| 2nd Highest Salary | |
| Experiment Validity | |
| Bagging vs Boosting | |
| Merge Sorted Lists | |
| P-value to a Layman | |
| Find the Missing Number | |
| Variable Error | |
| Scrambled Tickets | |
| Compute Deviation | |
| Prime to N | |
| String Shift | |
| 500 Cards | |
| Maximum Profit | |
| Nearest Common Ancestor | |
| Rain in N Days | |
| Find the First Non-Repeating Character in a String | |
| Button AB Test | |
| Success Measurement | |
| Target Indices | |
| Alphabet Sum | |
| Bank Fraud Model | |
| Rectangle Overlap | |
| Swipe Precision | |
| Radix Addition | |
| Over 100 Dollars |
Synthesized from candidate reports. Individual experiences may vary.
Candidates are first contacted by email and asked to complete a pre-recorded interview as an early screening step. This round focuses on initial fit and judgment rather than deep technical evaluation.
A live video call with interviewers described as friendly, with a smooth conversational tone. At least one broad judgment-based question was asked, such as an opinion on whether sanctions are good, suggesting the focus is on reasoning and perspective rather than purely technical skills.
Shortly after the video interview, candidates receive a take-home assignment with a tight two-day turnaround. Successful completion was indicated as the gateway to next steps, though communication after submission can be inconsistent.