← Sig Interview Insights

Sig·Software Engineer·Recruiter / HR Screen·Junior

JuniorPending
Jun 2026

Summary

Early stages of the SIG trading system engineering internship process. The recruiter call was low-key, just motivation and a light probability question, with a C++ live coding round coming up next.

Questions Asked (2)

Q1

Why are you interested in this role and company?

Adaptability & Ambiguity
Author's notes

Pretty standard stuff, recruiter was chill about it.

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AI HintsAI Generated

Suggested Approach

Connect your personal interests and career goals to the company's mission and the role's responsibilities, emphasizing how you thrive in ambiguous, fast-paced environments. Show that you've done your research and can articulate specific reasons why Sig is the right place for you to grow and contribute.

Pro tip: Mention a recent company announcement or product update and tie it to your own experience or skills, demonstrating genuine engagement and proactive research. This shows you're not just looking for any job, but specifically want to be part of Sig's journey.

1. Express enthusiasm for the company's mission

Start by stating what specifically excites you about Sig's mission, product, or culture, using details from your research.

2. Align with the role's requirements

Explain how your skills and experiences match the Software Engineer role, particularly in handling ambiguity and adapting to change.

3. Highlight your adaptability

Give a brief example of a time you successfully navigated ambiguity or a rapidly changing situation, linking it to the company's environment.

4. Connect to long-term goals

Share how this role fits into your career aspirations and how you see yourself growing with Sig.

5. Close with a forward-looking statement

Summarize why you're excited to contribute and ask a thoughtful question about the team or company to show continued interest.

Key Points to Mention

  • Specific aspects of Sig's mission, product, or recent news that resonate with you
  • Your experience working in ambiguous or fast-changing environments
  • How your technical skills align with the role's requirements
  • Examples of adaptability and problem-solving in past projects
  • Your desire to contribute to and grow with the company
  • A thoughtful question about the team or company to engage the interviewer

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

A basic probability question (specific details not shared).

Algorithms & Data Structures
Author's notes

Described as easy, no details given.

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AI HintsAI Generated

Suggested Approach

Clarify the exact probability question and any assumptions (e.g., independence, uniform distribution) before solving. Then break the problem into sample space and event, compute probabilities using combinatorics or conditional probability, and verify with a simple simulation or edge case.

Pro tip: State your assumptions explicitly and consider edge cases (e.g., with/without replacement) to show rigor. If time permits, mention how you'd verify the result with a quick Monte Carlo simulation.

1. Clarify the problem

Ask clarifying questions to ensure you understand the exact scenario, including any implicit assumptions (e.g., independence, fairness).

2. Define sample space and events

Identify all possible outcomes and the specific event(s) whose probability you need to compute.

3. Choose a method

Decide whether to use combinatorics, conditional probability, Bayes' theorem, or another approach based on the problem structure.

4. Compute and simplify

Perform the calculation step by step, simplifying fractions or expressions where possible.

5. Verify and interpret

Check the result for reasonableness (e.g., probability between 0 and 1) and consider edge cases or alternative methods to confirm.

Key Points to Mention

  • Independence and mutual exclusivity
  • Combinatorial counting (permutations/combinations)
  • Conditional probability and Bayes' theorem
  • Law of total probability
  • Expected value and variance (if relevant)
  • Simulation or Monte Carlo verification

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.