Voyage Advisory is a dynamic consultancy that thrives on solving complex business challenges through data science and analytics. We are seeking exceptional Data Scientists who are passionate about harnessing the power of data to drive meaningful insights and results for our clients. These dedicated professionals will engage in a variety of tasks, including applying Natural Language Processing (NLP) and Machine Learning (ML) to customer data, developing AI models, and crafting data products to uncover business insights.

In this guide, Interview Query will walk you through the interview process, key responsibilities, and the skills needed for the Data Scientist role at Voyage Advisory. Get ready to dive into your next career opportunity with confidence.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Voyage Advisory as a Data Scientist. Whether you were contacted by a Voyage Advisory recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Voyage Advisory Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Voyage Advisory data scientist hiring manager may be present during the screening round to answer your queries about the role and the company itself. They may also engage in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Voyage Advisory Data Scientist role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Voyage Advisory’s data systems, ETL pipelines, and SQL queries.

In the case of Data Scientist roles, take-home assignments regarding product metrics, analytics, and data visualization are incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Voyage Advisory office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the shortlisted candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Data Scientist role at Voyage Advisory.

Quick Tips For Voyage Advisory Data Scientist Interviews

• Master NLP and ML Techniques: Given the job description emphasizes a strong foundation in NLP, ML, and AI, brush up on these areas extensively. Utilize resources from Interview Query to tackle relevant problem sets and mock interviews.

• Quantitative Proficiency: Voyage Advisory places a strong focus on quantitative skills and the ability to draw insights from complex datasets. Make sure you're comfortable with statistical modeling, SQL queries, and Python programming.

• Client Communication: Given the consulting nature of the role, communication skills are crucial. Be prepared to translate technical jargon into actionable insights for clients. Role-play client scenarios to better prepare for these aspects of the interview.

Typically, interviews at Voyage Advisory vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• How would you set up an A/B test for button color and position changes? 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 set up this test to measure the impact on click-through rates?

• How would you forecast Facebook's revenue for the next year? You work on the revenue forecasting team at a company like Facebook. An executive asks you to forecast the company's revenue for the coming year. How would you approach this task?

• How would you investigate if the redesigned email campaign led to an increase in conversion rates? An E-commerce store's new marketing manager redesigned the new-user email journey, and the conversion rate increased from 40% to 43%. However, the rate was 45% a few months prior. How would you determine if the redesign caused the increase or if other factors were involved?

• How would you ensure data quality across different ETL platforms for PayPal's market research? PayPal partnered with a local survey platform for market research in Southern Africa, requiring data storage within each country's borders. The ETL pipeline connects PayPal’s data marts with the survey platform’s data warehouses, including translation modules. How would you ensure data quality across these ETL platforms?

• How would you conduct an experiment to test Uber's new ETA range feature? A PM at Uber is considering a new feature that displays an ETA range (e.g., 3-7 minutes) instead of a direct estimate (e.g., 5 minutes). How would you conduct this experiment and determine if the results are significant?

• Write a function min_distance to calculate the minimum absolute distance between two elements in an array and return all pairs with that difference. Given an array of integers, write a function min_distance to calculate the minimum absolute distance between two elements and return all pairs having that absolute difference. Ensure the pairs are returned in ascending order.

• Write a query to select the top five most expensive projects by budget to employee count ratio, accounting for duplicate rows in the employee_projects table. We have two tables: projects and employee_projects. Write a query to select the top five most expensive projects by budget to employee count ratio, considering the existence of duplicate rows in the employee_projects table.

• Write a function to simulate drawing balls from a jar. Given a list jar with ball colors and a list n_balls with corresponding counts, write a function to simulate drawing a ball from the jar.

• Design three classes: text_editor, moving_text_editor, and smart_text_editor with specific functionalities. Design three classes: text_editor, moving_text_editor, and smart_text_editor. Each class should have specific methods and functionalities as defined.

• Write a query to determine the top 5 actions performed during the week of Thanksgiving and rank them. The events table tracks user actions on a platform. Write a query to determine the top 5 actions performed during the week of Thanksgiving (11/22/2020 - 11/28/2020) and rank them based on the number of times performed.

• How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to a non-technical person, focusing on its role in determining the significance of results in hypothesis testing.

• What is the probability that it's actually raining in Seattle given your friends' responses? You called 3 friends in Seattle to ask if it's raining. Each has a 2/3 chance of telling the truth and a 1/3 chance of lying. All 3 said "Yes." Calculate the probability that it is actually raining.

• What is the probability of drawing three cards in increasing order from a shuffled deck of 500 cards? Imagine a deck of 500 cards numbered from 1 to 500. If you pick three cards one at a time, what is the probability that each subsequent card is larger than the previous one?

• How would you test if survey responses were filled at random by certain individuals? You have survey data from multiple-choice questions. Describe how you would test if some individuals filled out the survey randomly rather than truthfully.

• What is the probability of a biased coin landing heads exactly 5 times out of 6 tosses? Given a biased coin that lands heads 30% of the time, calculate the probability of it landing heads exactly 5 times in 6 tosses.

• What kind of model did the co-worker develop for loan approval? Your co-worker developed a model that takes customer inputs and returns a decision on whether a loan should be given or not. What type of model is this?

• How would you compare two credit risk models for predicting loan defaults? Given that personal loans are monthly installments, how would you measure the difference between two credit risk models within a specific timeframe?

• What metrics would you track to measure the success of a new credit risk model? Identify the key metrics you would track to evaluate the performance of a new credit risk model.

• 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.

• How would you detect firearm listings on a marketplace? Design a system to automatically detect if a listing on your website's marketplace is selling a gun, given that selling firearms is prohibited.

• How would you design a model to map legal first names to likely nicknames? As a data scientist at Facebook, you need to generate a machine learning model that maps legal first names to likely nicknames. How would you approach designing this model?

• How would you tackle multicollinearity in multiple linear regression? Explain the methods you would use to address multicollinearity in a multiple linear regression model.

If you want more insights about the company, check out our main Voyage Advisory Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Voyage Advisory’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Voyage Advisory Data Scientist interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!