I applied online. I interviewed at Two Sigma (New York, NY)
Interview
1. Three-hour HackerRank with an algorithm-writing problem and a data science problem
2. Three video interviews with quant researchers on data analysis, coding/algorithms, and core statistics
3. Interviews with hiring managers, questions are technical and team-specific, but also looking for culture fit
Interview questions [2]
Question 1
The data analysis interview asks you how you would predict some number. First you go through data ideation (if you could gather any reasonable data, what would you want?), then you talk about how you would go about engineering features and cleaning your data, then you talk about what kind of model you would use and why. They really drill into your answers, and you are likely not going to pass if you don't have a lot of experience in predictive modeling. Watch the mock interview video on their website for an easy example of what this is like.
The problems in the coding interview are not difficult for someone with a programming background. The interviewer asked me to evaluate the time-complexity and space-complexity of the algorithm and optimize it.
Discuss in an hour on how to predict house price starting with a initial dataset. Back and forth as the discussion go deeper. Discussed model choices, variable selection, and model validation, etc.
Interview questions [1]
Question 1
predict house price starting with a initial dataset
OA: Three coding questions (Linear Interpolator, Linear regression of daily temperature by town, Efficient fitting of linear regression)
3 Technical Interviews (1 hour each): 1. Data Analysis; 2. Coding and Algorithms; 3. Domain knowledge for Phd or Core Statistics
Final round with 2-3 hiring managers and a senior manager from matched teams: combination of open-ended technical problems and behavioral questions
Purely behavioral round with HR team and a recruiter
Interview questions [1]
Question 1
First round technical interview: begin with some questions about stats/probability knowledge, and the core is an open-ended case study
Three Technical:
Data analysis
- Approach to open-ended problem
o Paper, pen
- Ask interviewer if stuck
- Systematic manner:
o Creative ideas
o Technical proficiencies
o What sort of datasets
o What sort of features
o Technical / methodology
o Start with linear model first
- No code
Algorithms
- Hackerrank
o Short, simple and clean code
Core statistics / domain expertise
- Bachelor / Masters – core statistics
o Linear regression
o R^2
o T-stat
o How they are used
o Statistics foundation
- No code
Two more rounds of intern / hiring managers:
- Mainly technical, some behavioral
o Similar to data analysis
o More targeted towards their team
o Come prepared with questions
If well, 30 min technical interview:
- Logistical interview
30 min of senior meeting with Two Sigma:
- Cultural fit
o Behavioral mainly
o Maybe 1 technical
Team match in the spring for more accurate project matching
Tested on foundational knowledge
