Denali Advanced Integration is a cutting-edge technology solutions provider known for delivering comprehensive IT services and solutions across diverse industries. The company is dedicated to driving innovation and helping businesses scale through advanced integration and strategic technological implementations.

As a Data Scientist at Denali Advanced Integration, you'll be diving deep into data analysis, employing machine learning techniques, and contributing to data-driven decision-making processes that propel client success. This role demands a robust understanding of statistical analysis, data mining, and predictive modeling to effectively interpret complex data sets and generate actionable insights.

If you're considering a career as a Data Scientist with Denali Advanced Integration, this guide is designed to assist you. We’ll cover the interview process, frequently asked questions, and essential tips to help you succeed. Let’s dive in!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Denali Advanced Integration as a Data Scientist. Whether you were contacted by a Denali 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 Denali 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 Denali 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 Denali 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 Denali’s data systems, ETL pipelines, and SQL queries.

In the case of data scientist roles, take-home assignments regarding machine learning models, data analysis, 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 Denali 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 Denali.

Quick Tips For Denali Advanced Integration Data Scientist Interviews

• Understand Denali's Services: Familiarize yourself with Denali's technologies, services, and industry focus. This knowledge will help you tailor your answers to align with the company's needs.
• Be Problem-Solving Oriented: Denali values candidates who can identify and solve complex data problems. Practice solving a variety of data science problems and be prepared to discuss your problem-solving approach.
• Highlight Collaboration Skills: Show your ability to work collaboratively with different teams. Denali values inter-departmental cooperation, so be prepared to discuss your experiences working in team settings.

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

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• Write a function to find the maximum number in a list of integers. Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return None.

• Create a function convert_to_bst to convert a sorted list into a balanced binary tree. Given a sorted list, create a function convert_to_bst that converts the list into a balanced binary tree. The output binary tree should have a height difference of at most one between the left and right subtrees of all nodes.

• Write a function to simulate drawing balls from a jar. Write a function to simulate drawing balls from a jar. The colors of the balls are stored in a list named jar, with corresponding counts of the balls stored in the same index in a list called n_balls.

• Develop a function can_shift to determine if one string can be shifted to become another. Given two strings A and B, write a function can_shift to return whether or not A can be shifted some number of places to get B.

• What are the drawbacks of the given data organization, and how would you reformat it for better analysis? Assume you have data on student test scores in two different layouts. Identify the drawbacks of these layouts and suggest formatting changes to make the data more useful for analysis. Additionally, describe common problems seen in "messy" datasets.

• How would you locate a mouse in a 4x4 grid using the fewest scans? You have a 4x4 grid with a mouse trapped in one of the cells. You can scan subsets of cells to know if the mouse is within that subset. Describe a strategy to find the mouse using the fewest number of scans.

• How would you select Dashers for Doordash deliveries in NYC and Charlotte? Doordash is launching delivery services in NYC and Charlotte and needs a process for selecting dashers. Describe how you would decide which dashers to select and whether the criteria would be the same for both cities.

• What factors could bias Jetco's boarding time study, and what would you investigate? Jetco, a new airline, has the fastest average boarding times according to a study. Identify potential factors that could have biased this result and what you would look into to verify the findings.

• How would you design an A/B test to evaluate a pricing increase for a B2B SAAS company? A B2B SAAS company wants to test different subscription pricing levels. Describe how you would design a two-week A/B test to evaluate a pricing increase and determine if it is a good business decision.

• How much should we budget for a $5 coupon initiative in a ride-sharing app? A ride-sharing app has a probability (p) of dispensing a $5 coupon to a rider and services (N) riders. Calculate the total budget needed for the coupon initiative.

• What is the probability of both or only one rider getting a coupon? A driver using the app picks up two passengers. Determine the probability of both riders getting the coupon and the probability that only one of them will get the coupon.

• What is a confidence interval for a statistic and why is it useful? Explain what a confidence interval is, why it is useful to know the confidence interval for a statistic, and how to calculate it.

• What is the probability that item X is found on Amazon's website? Given that item X has a probability of 0.6 of being available at warehouse A and 0.8 at warehouse B, calculate the probability that item X would be found on Amazon's website.

• Is a coin fair if it comes up tails 8 times out of 10 flips? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if this coin is fair.

• What are time series models and why are they needed? Describe what time series models are and explain why they are necessary when less complicated regression models are available.

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

• How would you evaluate and deploy a decision tree model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will repay a personal loan. How would you evaluate if a decision tree is the correct model? How would you evaluate its performance before and after deployment?

• How does random forest generate the forest and why use it over logistic regression? Explain how random forest generates its forest. Additionally, why would you choose random forest over other algorithms like logistic regression?

• How would you explain linear regression to a child, a first-year college student, and a seasoned mathematician? 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 each audience's understanding level.

• What are the key differences between classification models and regression models? Describe the main differences between classification models and regression models.

As you prepare to embark on your career journey with Denali Advanced Integration as a Data Scientist, it's essential to fully equip yourself for the interview process. For more tailored insights about the company, dive into our comprehensive Denali Advanced Integration Interview Guide, where we have meticulously covered many potential interview questions. Additionally, explore our other role-specific guides such as software engineer and data analyst to gain a broader perspective on Denali Advanced Integration’s interview processes.

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 any interview question and challenge presented by Denali Advanced Integration.

For even more preparation, check out all our company interview guides. If you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!