Technical Resources International, Inc. (TRI) is renowned for providing high-quality technical and professional services, making a significant impact across federal and commercial sectors. Their commitment to innovation and excellence has established them as leaders in their industry.

Securing a position as a Data Scientist at TRI involves navigating a challenging and rigorous interview process. The role demands expertise in data manipulation, statistical analysis, machine learning, and a deep understanding of algorithms. As a Data Scientist, you will utilize your technical skills to drive data-driven decision-making and solve complex problems.

In collaboration with Interview Query, we are excited to present this guide to help you prepare effectively. Whether it's understanding the interview stages or practicing key problems, this guide is designed to set you on the path to success. Let's delve into the specifics of acing your TRI Data Scientist interview!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Technical Resources International, Inc. as a Data Scientist. Whether you were contacted by a TRI 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 TRI 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 TRI data scientist hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge 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 TRI 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 TRI’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 TRI office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized 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 TRI.

Quick Tips For Technical Resources International, Inc. Data Scientist Interviews

• Understand TRI’s Focus Areas: Familiarize yourself with the company's projects and sectors they operate in. Being well-versed with TRI's areas of specialization helps in tackling domain-specific questions.
• Revise Your Technical Foundations: Data science interviews can span a variety of topics. Ensure you review SQL queries, machine learning algorithms, hypothesis testing, and data visualization.
• Prepare for Behavioral Questions: TRI values teamwork and effective communication. Practice answering behavioral questions that highlight your collaboration skills and how you’ve applied your technical knowledge in past roles.

Typically, interviews at Technical Resources International, Inc. vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• Create a function max_substring to find the maximal substring shared by two strings. Given two strings, string1 and string2, write a function max_substring to return the maximal substring shared by both strings. If there are multiple max substrings with the same length, return any one of them.

• Develop a function moving_window to find the moving window average of a list of numbers. Given a list of numbers nums and an integer window_size, write a function moving_window to find the moving window average.

• Write a function to determine if a string is a palindrome. Given a string, write a function to determine if it is a palindrome — a word that reads the same forwards and backwards.

• Write a query to find users currently "Excited" and never "Bored" with a campaign. You have a table of users' impressions of ad campaigns over time. Each impression_id consists of values of user engagement specified by Excited, OK, and Bored. Write a query to find all users that are currently "Excited" and have never been "Bored" with a campaign.

• Create a function search_list to check if a target value is in a linked list. Write a function, search_list, that returns a boolean indicating if the target value is in the linked_list or not. You receive the head of the linked list, which is a dictionary with keys value and next. If the linked list is empty, you'll receive None.

• 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 these results?

• What considerations should be made when testing hundreds of hypotheses with many t-tests? You are testing hundreds of hypotheses using multiple t-tests. What factors should you consider to ensure the validity of your results?

• How would you generate a daily report and evaluate campaign performance for the first 7 days? Given a schema representing advertiser campaigns and impressions, generate a daily report for the first 7 days. Evaluate campaign performance and identify which promos need attention using a specific heuristic.

• How would you investigate if a redesigned email campaign led to an increase in conversion rates? A new marketing manager redesigned the new-user email journey, and conversion rates 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?

• What kind of analysis would you conduct to recommend UI changes for a community forum app? You have access to tables summarizing user event data for a community forum app. What analysis would you perform to recommend improvements to the user interface?

• 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?

• What is the downside of only using the R-Squared ((R^2)) value to determine a relationship between two variables? You are analyzing how well a model fits the data and want to determine a relationship between two variables. What are the limitations of relying solely on the R-Squared value?

• Is a coin that comes up tails 8 times and heads twice in 10 flips fair? You flip a coin 10 times, resulting in 8 tails and 2 heads. Is this coin fair?

• 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 someone without a technical background.

• What’s the probability that (2X > Y) given two independent standard normal random variables (X) and (Y)? Given two independent standard normal random variables (X) and (Y), calculate the probability that (2X > Y).

• How would you build a fraud detection model using a dataset of 600,000 credit card transactions? Imagine you work at a major credit card company and are given a dataset of 600,000 credit card transactions. Describe your approach to building a fraud detection model in the comments.

• How does random forest generate the forest and why use it over logistic regression? Explain the process of how a random forest generates its forest. Additionally, discuss why one might choose random forest over other algorithms such as logistic regression.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. Describe a scenario where you would use a bagging algorithm and another where you would use a boosting algorithm. Provide examples of the tradeoffs between the two.

• How would you evaluate and compare two credit risk models for personal loans?

• Identify the type of model your co-worker developed to determine loan eligibility.
• Given that personal loans are monthly installments, describe how you would measure the difference between two credit risk models within a timeframe.

• List the metrics you would track to measure the success of the new model.

• How would you explain linear regression to different audiences? Explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician. Tailor your explanations to the understanding level of each audience.

Embarking on a career as a Data Scientist at Technical Resources International, Inc. promises an engaging challenge that marries technical proficiency with impactful project work. If you want more insights about the company, check out our main Technical Resources International, Inc. 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 the 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 Technical Resources International, Inc. 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!