Top 22 Optiver Data Analyst Interview Questions + Guide in 2024

Financial markets rely on market makers like Optiver to remain efficient in all conditions. This is a role Optiver cannot serve today without turning to data analytics. This has made the company a premier destination for data analysts.

Interviewing for a data analyst position at Optiver is very competitive. You may feel overwhelmed by its process if you don’t know what to expect.

With this guide, we provide sample Optiver data analyst interview questions designed to assist aspirees in successfully navigating their application.

There are typically four interview rounds, and some rounds comprise several sub-interviews. Candidates are eliminated at every round, and not every interview will proceed in this order.

Application

You can apply for jobs through Optiver’s career opportunities page, through your university or college, or through a recruiter. You can also be referred by existing employees.

Online Cognitive Testing

This interview round is done using platforms like SHL. The purpose of this round is to determine candidates’ cognitive abilities. Skills tested include numerical, deductive, and inductive reasoning.

Interview With HR or Recruiter

This interview aims to figure out your personality and motivations, as well as how well you’d fit in with the culture at Optiver. The interview may be done by HR or a recruiter.

Technical Interview

This interview may be over the phone or in person. You may be asked to come up with an algorithm to quantify something, perform statistical analysis on data, solve an estimation question, etc. This interview may take several hours.

Take-Home Assignment

The takehome assignment is a longer problem, e.g., on coding. You may be asked questions about the assignment during subsequent interviews to explain the decisions you made or explain how your solutions would work in different situations.

Final Interview

You should expect more than one sub-interview during the final round. Expect to be asked follow-up questions on the takehome assignment and other technical questions. You’ll likely have another HR interview and other tests before the company decides whether to submit an offer or not.

During an Optiver Data Analyst interview, candidates may face a variety of questions. These can cover topics like market-making, dealing with failure, and reasons for favoring Optiver over competitors. Staying updated on financial news, handling outliers in datasets, and explaining complex concepts like neural networks in simple terms is also important.

For a more in-depth discussion, look through our list below as we’ve dove deep into the possible interview questions being asked for Optiver’s data analyst role:

1. What does a market maker do?

This question tests how well you have researched and understood the role of Optiver in financial markets. As an Optiver data analyst, your work will play a key role in market making.

How to Answer

Provide an answer that shows you understand the basic definition of a market maker, and give an example to demonstrate that you understand the role behind the definition.

Example

“Market makers are entities that partner with exchanges to ensure there is liquidity by acting as buyers and sellers for all securities on the exchange. They ensure there’s always a buyer and a seller for security, keeping the exchange efficient. If you wanted to sell the shares of a low-volume stock immediately, market makers can buy them to ensure you don’t have to wait until another investor shows up.”

2. Tell me about a time you failed.

As a data analyst, you’ll probably make mistakes from time to time. At a demanding company like Optiver, they’ll want to know if you’re able to bounce back from such mistakes by being resilient and open to learning and receiving criticism.

How to Answer

Focus on the lessons learned and not the failure, and choose a scenario that can be regarded as a reasonable miscalculation and not a failure due to personal flaws. Don’t try to defend the failure, but choose words that show you’re now looking at the experience from a positive point of view.

Example

“My team and I were supposed to come up with a new algorithm but in the last month, we realized we were not going to make the deadline. We had miscalculated how much time we’d need to test the new model. As a result, we had to work overtime, including weekends to ensure the new algorithm was ready in time. Due to that experience, we became better at planning and scheduling tasks for projects.”

3. Why do you want to work for us instead of our competitors?

Interviewers will want to know why you specifically chose the data analyst role at Optiver. They want to establish if you’re passionate about working for the company because of its culture and values or if your interest is only temporary.

How to Answer

Your answer should cover why you chose the company and role and why you’re a good match for both. Avoid lying or being negative in your response. Additionally, focus on how your presence benefits both parties.

Example

“Optiver is a market maker in several markets all over the world, and the growth and learning opportunities are immense. I believe my expertise as a data analyst will grow faster in a fast-paced company such as this because I can get almost constant feedback on my analytics work. I am passionate about developing and testing new algorithms and trying to get better results each time.”

4. Where do you follow the financial news?

Optiver’s data analysts must be aware of what is happening in the finance industry because it influences their work every day. Interviewers will want to know if you’re motivated enough to keep track of what is going on and whether the information you get is reliable.

How to Answer

Your top answer should be a well-known organization. 24-hour business-oriented stations or regularly updated business/financial news sites. You should also point to the increasing importance of social media in delivering news but it shouldn’t be your primary news source.

Example

“I regularly tune in to the CNBC and Bloomberg news channels. I also follow them on Twitter so I can keep up with any breaking news on the go. I’ve also been subscribed to the Morning Brew newsletter for the past two years.”

5. How would you handle outliers in a dataset?

Optiver receives a massive amount of data daily, and data analysts have to ensure the data undergoes the necessary preprocessing steps. Handling outliers is a common challenge in data preprocessing, and this question tests if you know how to deal with them.

How to Answer

There are established methods for dealing with outliers in data. You can keep your answer brief and to the point, focusing on the main ways outliers are handled in datasets.

Example

“I handle outliers differently depending on the scenario. Filtering them out works well if the outlier is likely an error. Swapping the outliers with the mean or median is also an alternative. I could also apply a different transformation that brings the outliers closer to the other points if necessary.”

6. How would you explain neural networks to children in a simple way?

This question assesses your ability as a data analyst to communicate complex concepts, like machine learning, in simple terms. This skill is crucial at Optiver, where explaining data-driven strategies in an understandable way is key for collaborative work.

How to Answer

Use analogies and simple terms to describe neural networks, avoiding technical jargon.

Example

“I would compare neural networks to how we learn to recognize different animals. Each part of the network contributes a little bit, just like each child in a class adds a small piece of information.”

7. Which model would you use to evaluate the performance of two people playing tennis?

As a data analyst at Optiver, you’ll have to determine which models are better suited for training the available data and making predictions. This question tests if you know how to choose a suitable model depending on the scenario.

How to Answer

Identify the primary purpose of the model before making a choice. In this case, it would be predicting which of the two players will win the match. Therefore, the best model is likely one that can be used to predict the probability of one of two outcomes.

Example

“Assuming the model’s main purpose was to predict which of the two players was going to win, a logistic regression model would be well-suited for this scenario. We can use data such as who serves first, average serve speed, players’ builds, ages, etc. as the predictive variables for the model.”

8. How do you assess the success of an A/B test on free shipping mentions in increasing conversions?

This question tests your data analytic skills in statistical analysis and decision-making based on data, essential for optimizing strategies in Optiver’s trading environment.

How to Answer

Explain evaluating the statistical significance of the conversion rate differences between control and experiment groups.

Example

“I would calculate the conversion rate for both groups and then use a statistical significance test, like a t-test, to see if the increase in the experiment group is statistically significant compared to the control group. This helps confirm if the free shipping offer genuinely impacted customer behavior.”

9. What is the expected number of coin flips required to get two consecutive heads?

Probability theory and concepts like mathematical expectation help data analysts at Optiver to make decisions. This type of question tests if you can apply that knowledge in a specific scenario.

How to Answer

Consider the possible outcomes when the coin is flipped twice and how many more flips will be required after the first two flips to achieve the desired outcome.

Example

“If x is the number of flips needed to get to the first heads, a tail on the first flip has a probability of ¹⁄₂, and it means we’ll need x+1 flips. A heads on the first and a tails on the second flip means we’ll need x+2 flips. This has a probability of ¹⁄₂¹⁄₂ = ¹⁄₄. The probability of two heads on the first two flips is ¹⁄₂¹⁄₂ = ¹⁄₄. These three cases can be put in the form of an equation where x=(¹⁄₂)(x+1)+(¹⁄₄)(x+2)+¹⁄₄(2). Solving for x, we get that x=6.”

10. How can you analyze focus group data to select TV series pilots for streaming?

While indirectly related, this question evaluates your skill as a data analyst to handle and interpret qualitative data, a skill valuable for analyzing market trends and consumer behavior at Optiver.

How to Answer

Discuss how to analyze ratings, variability, and audience preferences to determine the most appealing TV pilots.

Example

“I would start by calculating the average rating for each pilot. Then, I’d segment the data by demographics to see if certain pilots appeal more to specific groups. Finally, I’d analyze any written feedback to identify common themes or specific elements that participants liked or disliked.”

11. If you have a single deck of cards, what is the probability of drawing two cards of the same suite?

This question also tests if you can apply your knowledge of probability theory to solve problems. The analytics work at Optiver is partially built on an understanding of these fundamentals.

How to Answer

Your answer should show that you understand the changes that occur when a card is drawn from a single deck. You also need to know the probability of specific events happening and how these probabilities are affected by preceding events.

Example

“For dependent events, the probability of event A and B taking place is the same as the probability of event A happening multiplied by the probability of event B taking place given that event A already happened. The probability of drawing a card of one suite is ¹³⁄₅₂. The probability of drawing a second card of the same suite is thus ¹²⁄₅₁. Since there are four possible suites, the probability of drawing two cards of the same suite is 4¹³⁄₅₂¹²⁄₅₁ = ⁴⁄₁₇.”

12. How would you analyze churn behavior in different pricing plans?

This question explores your ability to analyze customer retention, applicable to Optiver for understanding trader behavior and platform engagement.

How to Answer

Explain using metrics like churn rate, customer lifetime value, and engagement patterns to analyze subscription performance.

Example

“I’d calculate churn rates for each pricing plan, assess customer lifetime value, and analyze engagement trends to understand what influences customer retention and subscription preferences.”

13. What is the probability of getting 3 heads in 7 coin flips?

This question tests your knowledge of probability distributions, a key concept in statistics. Data analysts at Optiver are required to have a good understanding of probability distributions and when to apply them to make predictions in uncertain circumstances.

How to Answer

The most important step is identifying the type of distribution you’re working with so you can easily use its formula to solve the problem. In this case, we are dealing with a binomial distribution, so you can plug the values into the corresponding equation.

Example

“Predicting the probability of x events in y number of trials points to a binomial distribution. The number of events, n, is 7, and the number of success, k, is 1. The probability of success in each event is ¹⁄₂. Plugging these values into the equation, we find that the probability of getting 3 heads in 7 flips is 0.2734”

14. What approach would you use to analyze focus group data for TV series pilots?

This question assesses your data analysis skills in a non-traditional context, reflecting the diverse data challenges a Data Analyst may encounter at Optiver.

How to Answer

Discuss quantitative and qualitative data analysis methods like averaging ratings and thematic analysis of feedback.

Example

“I would calculate mean ratings for each pilot and perform a thematic analysis of participant feedback, looking for patterns and preferences to identify the most promising pilots.”

15. What’s the difference between type I and type II errors in hypothesis testing?

Interviewers consider knowledge of these definitions to be fundamental for data professionals. When interviewing for a data analyst position at Optiver, you’ll be expected to know the ins and outs of hypothesis testing, including the errors that can be made.

How to Answer

Type I and type II errors are well-defined concepts so you can offer short and simple definitions of the same.

Example

“Type I errors are also known as false positives. These are cases where the null hypothesis is rejected despite being true. False negatives or type II errors are cases where false null hypotheses are not rejected.”

16. How do you create a model for bidding on unseen keywords?

This question is relevant for understanding your skills in machine learning and optimization, important for developing algorithms at Optiver as a data analyst.

How to Answer

Describe using a supervised learning algorithm and the generation of word embeddings to inform keyword bidding.

Example

“I would use a supervised learning algorithm, starting with text preprocessing to create word embeddings from the keywords. Then, I’d employ a model like a neural network to predict the optimal bidding price based on these embeddings. The model would be trained on historical bidding data and continuously updated to adapt to new trends.”

17. What steps would you take to diagnose an underpricing algorithm?

This question tests your data analytic problem-solving skills and algorithm optimization abilities, paralleling challenges in financial data analysis and trading strategy optimization at Optiver.

How to Answer

Outline a systematic approach to identify and correct the factors leading to underpricing.

Example

“I would first analyze the input data for accuracy, especially focusing on demand, availability, and logistics cost. Then, I would review the algorithm’s logic to identify any flaws or outdated assumptions. If necessary, I’d conduct a sensitivity analysis to understand how different variables impact pricing and adjust the algorithm accordingly.”

18. When presented with two models, one with 85% accuracy and the other with 82%, which one should you choose?

At Optiver, where nuanced decision-making based on model performance is key, this question probes deeper into your understanding of model evaluation, emphasizing that model selection involves more than just surface-level accuracy metrics as a data analyst.

How to Answer

Describe the importance of evaluating other performance metrics, such as precision, recall, and understanding the model’s application context. Discuss how these factors influence the choice beyond just the accuracy percentage.

Example

“While the 85% accuracy model seems better at first glance, I’d evaluate other metrics like precision and recall, especially in contexts where specific types of errors have different consequences. For instance, in a financial model where false positives are more costly, a model with lower overall accuracy but higher precision might be preferable.”

19. What methods can be used to forecast the electricity supply for a town?

This question evaluates your skills in time-series forecasting, crucial for a Data Analyst at Optiver in predicting market trends and managing risks.

How to Answer

Explain using time-series models like ARIMA to forecast electricity demand based on historical data and seasonality.

Example

“I’d use the ARIMA model to forecast electricity demand, accounting for seasonality and past consumption patterns. This model helps predict future demand with a focus on minimizing over or under-supply.”

20. How would you conduct a user journey analysis to recommend UI improvements?

This question tests your ability to analyze user interaction data, relevant for a Data Analyst at Optiver in optimizing trading platform interfaces for better user experience.

How to Answer

Detail methods like tracking user flow, engagement metrics, and dropout points to identify UI improvement areas.

Example

“I’d analyze user pathways, identify common entry and exit points, and measure engagement at various stages. This data helps pinpoint where users face difficulties, guiding UI enhancements.”

21. Write a query to get the number of days between each user’s first session and last session.

This question tests your ability to calculate the difference between users’ first and last sessions within a specific time frame, relevant for a Business Intelligence role at Amazon, where understanding user behavior over time is crucial for optimizing services and features.

How to Answer

Explain the steps to measure the date difference between the first and last user sessions using SQL functions. Highlight the use of aggregation and date functions to extract meaningful insights from user session data.

Example

“I’d utilize SQL to find the difference between the earliest and latest session dates for each user within 2020. By using functions like DATEDIFF, MIN, and MAX, combined with a WHERE clause to filter for the year, I can accurately calculate this difference. Grouping the results by user ID allows for a clear summary of each user’s session span, providing valuable insights into user engagement and retention patterns.”

22. How would you assess the validity the result of an AB test?

This question tests your ability to analyze the setup and measurement validity of an AB test, crucial for ensuring reliable and unbiased results in any data-driven decision-making process.

How to Answer

Discuss the importance of clarifying assumptions about the AB test upfront, emphasizing the need to understand how the test was set up and measured. Explain how to check for validity by examining user group separation and ensuring variants are equal in all aspects. Highlight the role of p-value measurement and the significance of determining the correct sample size and experiment duration.

Example

“To ensure AB test validity, I’d confirm user groups are correctly separated and traffic sources are balanced to avoid bias. I’d check that variants differ only in the tested aspect. For measurement, I would determine the proper sample size and duration before starting the test to avoid incorrect p-value readings from continuous monitoring.”

Preparing for your Optiver data analyst interview can be the difference between getting an offer and getting eliminated in the first round. Here are a few ways to improve your chances of success.

Do Your Research

Many of the questions test your knowledge of Optiver and the trading industry in general. Take the time to find out what Optiver does, its role in global finance, and even who its competitors are. This will help to show how your skills and motivations align with the company’s.

You should also check out Interview Query’s data analytics learning path to find out the areas that are typically covered by the questions asked in data analytics interviews.

Practice the Tests, Games, and Questions

Practice the types of questions you’re likely to encounter during your interview at Optiver. Many of these questions require practice for you to get better at answering them. You can find many interview questions tailored towards this position on Interview Query.

Do Mock Interviews

Mock interviews give you a chance to assess how well you vocalize the answers in your head. You may have the right answers, but your delivery may need improvement. You can sign up for a mock interview and get paired with other aspiring data professionals on Interview Query.

Show Your Thought Process When Answering Technical Questions

Interviewers are interested in the answers as well as the thought process that leads you to the answers. Think through your solutions before you jump in, and ensure the interviewers can follow your train of thought by explaining and justifying your decisions.

Interview Query’s coaching service can help you to get better at this. You can get guidance and tips from professionals to help you answer interview questions the right way.

These are some of the frequently asked questions by people interested in working as data analysts at Optiver.

How much do data analysts at Optiver make in a year?

You can check out the average base salary and the average total compensation for data analysts in general on Interview Query’s data analyst salary page.

Where can I read more about other people’s interview experiences for Optiver’s data analyst role here in Interview Query?

Interview Query does not have a section on interview experiences for data analyst roles at Optiver. However, you can read about other people’s interview experiences at other companies for different roles in our interview experiences section.

You can also interact with other aspiring and working data analysts in the IQ community on Slack.

Does Interview Query have job postings for Optiver’s data analyst role?

No, Interview Query does not directly list job postings for Optiver’s data analyst roles. For job postings, you might want to visit their official career page or job boards that specifically list data analyst positions.

You can also consider finding new opportunities for data analysts on Interview Query’s jobs board. It’s updated with the most recent job postings for data analyst roles in the largest companies in the world, and not just Optiver’s.

If you need more leads about the company, then try going through our main Optiver Interview Guide, where we’ve provided the main list of interview questions that you might hope to encounter. We’ve also covered their software engineering and data scientist roles, so consider going through those guides as well.

The constantly changing dynamics in market-making make a job at Optiver very attractive to data analysts, and that’s why here at Interview Query, we hope that with this guide and other resources we have, you can make great strides towards passing and acing your upcoming Optiver data analyst interview questions.

Don’t hesitate to reach out to us if you need any help, and be sure to check out our services, as they’re catered specifically to also help you with everything you need.