Bloomberg Product Manager Interview Questions + Guide in 2024

Bloomberg L.P. is a global leader in business and financial information, delivering data, news, and analytics to influential decision-makers across various industries. Renowned for its iconic Bloomberg Terminal, the company excels in providing real-time financial information and a wide range of tools to over 500,000 subscribers globally.

As a Product Manager at Bloomberg, your role will be pivotal in shaping, developing, and executing innovative products that meet the complex demands of the clients. You’ll work closely with cross-functional teams, from engineering to sales, to ensure their offerings deliver substantial value. Utilizing agile development processes, you will manage roadmaps, track strategic goals, and constantly engage with clients to refine product features based on real-world feedback.

In this guide, we’ll walk you through the interview process, and some commonly asked Bloomberg product manager interview questions. We will also provide invaluable tips to help you ace your interviews and land that product manager role. Let’s get started!

Recruiter Call Screening

Once your application has been reviewed and shortlisted, a recruiter from Bloomberg’s talent acquisition team will contact you for an initial screening call. This call typically lasts about 30 minutes and covers basic information about your background, experience, and interest in Bloomberg. Expect questions like:

• Describe yourself and your past experiences.
• Why are you interested in working at Bloomberg?
• What are your salary expectations and work authorization status?

Technical Virtual Interview

If you pass the recruiter screening, you will be invited to a technical virtual interview with the hiring manager. This interview usually lasts about an hour and covers role-specific details. You can expect questions on technical systems you have used, your understanding of relevant financial concepts, and situational scenarios you have faced in previous roles.

Sample questions include:

• Describe a time you went against senior management.
• How do you navigate a decline in engagement metrics?
• Explain your understanding of Agile product management.

Depending on the role, you may also be given a take-home case study or assignment.

Onsite Interview Rounds

After the technical interview, you may be invited for multiple onsite or virtual interview rounds. These rounds typically involve interviews with various team members, including future colleagues and department heads. Each interview usually lasts about 45-60 minutes.

Expect to discuss your background in-depth, answer behavioral and technical questions, and possibly present any take-home assignment you were given.

Sample questions include:

• Why do you want to work at Bloomberg?
• How would you start the job if hired?
• What is your understanding of our products/services?

Final Round and Offer

Once you have successfully navigated the multi-round interview process, you will be contacted by HR with feedback and, if successful, a formal job offer. The entire process may take around three weeks but can extend depending on various factors.

Typically, interviews at Bloomberg L.P. vary by role and team, but commonly Product Manager interviews follow a fairly standardized process across these question topics.

1. Would you think there was anything fishy about the results of an A/B test with 20 variants?

Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with the results?

2. How would you set up an A/B test to optimize button color and position for higher click-through rates?

A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

3. What would you do if friend requests on Facebook are down 10%?

A product manager at Facebook reports a 10% decrease in friend requests. What steps would you take to address this issue?

4. Why would the number of job applicants decrease while job postings remain the same?

You observe that the number of job postings per day has remained constant, but the number of applicants has steadily decreased. What could be the reasons for this trend?

5. What are the drawbacks of the given student test score datasets, and how would you reformat them for better analysis?

You have data on student test scores in two different layouts. What are the drawbacks of these formats, what changes would you make for better analysis, and what are common problems in “messy” datasets?

6. Write a function to determine if two strings are anagrams of each other.

Given two strings, write a function to return True if the strings are anagrams of each other and False if they are not. Note: A word is not an anagram of itself.

Example 1:

Input:

string_1 = "listen"
string_2 = "silent"

Output:

True

Example 2:

Input:

string_1 = "banana"
string_2 = "bandana"

Output:

False

7. Is this a fair coin?

You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if the coin is fair based on this outcome.

8. How do you write a function to calculate sample variance?

Write a function that outputs the sample variance given a list of integers. Round the result to 2 decimal places. Example input: test_list = [6, 7, 3, 9, 10, 15]. Example output: get_variance(test_list) -> 13.89.

9. Is there anything fishy about the A/B test results with 20 variants?

Your manager ran an A/B test with 20 different variants and found one significant result. Evaluate if there is anything suspicious about these results.

10. How do you find the median in a list with a majority repeating integer in O(1) time and space?

Given a list of sorted integers where more than 50% of the list is the same repeating integer, write a function to return the median value in O(1) computational time and space. Example input: li = [1,2,2]. Example output: median(li) -> 2.

11. What are the drawbacks and formatting changes needed for messy datasets?

You have data on student test scores in two different layouts (dataset 1 and dataset 2). Identify the drawbacks of these layouts, suggest formatting changes to make the data more useful for analysis, and describe common problems seen in messy datasets.

12. How would you evaluate whether using a decision tree algorithm is the correct model for predicting loan repayment?

You are tasked with building a decision tree model to predict if a borrower will pay back a personal loan. How would you evaluate if a decision tree is the right choice? Additionally, how would you evaluate the model’s performance before and after deployment?

13. How does random forest generate the forest and why use it over logistic regression?

Explain the process by which a random forest generates its forest. Additionally, discuss why one might choose random forest over logistic regression for certain problems.

14. When would you use a bagging algorithm versus a boosting algorithm?

Compare two machine learning algorithms. In which scenarios would you prefer a bagging algorithm over a boosting algorithm? Provide examples of the tradeoffs between the two.

15. How would you justify using a neural network for a business problem and explain its predictions to non-technical stakeholders?

Your manager asks you to build a model with a neural network to solve a business problem. How would you justify the complexity of this model and explain its predictions to non-technical stakeholders?

16. What metrics would you use to track the accuracy and validity of a spam classifier for emails?

You are tasked with building a spam classifier for emails and have completed a V1 of the model. What metrics would you use to track the model’s accuracy and validity?

Here are some proven tips to help you prepare for your upcoming interview at Bloomberg:

• Research Thoroughly: Understand Bloomberg’s various products and services, as they may come up during your interviews. Knowing the specifics can give you an edge.

• Prepare for a Variety of Questions: Be ready for both standard behavioral questions and more abstract, technical questions. This could include anything from fixed-income discussions to agile practices.

• Be Transparent About Your Goals: Bloomberg values candidates who understand how their career goals align with the company’s strategic objectives. Make sure to articulate this clearly.

• Do Mock Interview with Peers or AI: Nothing beats real-time feedback from other people to address what you need to improve and what you need to keep on doing. Try our mock interview or AI interviewer to start getting valuable insights.

What is the average salary for a Product Manager at Bloomberg Lp?

What is the company culture like at Bloomberg?

Bloomberg’s culture is fast-paced and collaborative, like a newsroom or trading floor. The environment encourages innovation and teamwork, strongly emphasizing quality and accuracy. The company values diversity and inclusivity, providing volunteer opportunities and community engagement projects. It’s an open culture that supports learning, taking risks, and thinking outside the box.

Are there any job openings at Bloomberg?

As of writing, Bloomberg is currently looking for a product manager! To check out current openings, head over to our Job Board for more information.

As Bloomberg LP continues to redefine the landscape of financial data and technology, the Product Manager’s role stands out as a key driver of innovation and success.

By showcasing your technical expertise, understanding of market dynamics, and strategic vision, you’ll position yourself as the ideal candidate to lead Bloomberg’s product initiatives.

We wish you the best on the interview!